From skalsky@public.btr.com Thu Jan 6 18:32:59 EST 1994 Article: 20115 of comp.ai Xref: glinda.oz.cs.cmu.edu comp.ai:20115 Path: honeydew.srv.cs.cmu.edu!fs7.ece.cmu.edu!europa.eng.gtefsd.com!uunet!openlink.openlink.com!public!skalsky From: skalsky@public.btr.com (Rick Skalsky UUCPR ed aaai.org skalsky@btr.com) Newsgroups: comp.ai Subject: AAAI-94 Conference Workshops Date: 5 Jan 1994 22:23:44 GMT Organization: OpenLink, Inc Lines: 1587 Message-ID: <2gfelg$7a9@openlink.openlink.com> NNTP-Posting-Host: public.btr.com Keywords: AAAI-94 Seattle, WA workshops Twelfth National Conference on Artificial Intelligence (AAAI-94) Workshop Program July 31-August 4, 1994 Seattle, Washington Sponsored by the American Association for Artificial Intelligence 445 Burgess Drive, Menlo Park, CA 94025 (415) 328-3123 workshops@aaai.org AAAI is pleased to present the AAAI-94 Workshops Series. Workshops will be held Sunday - Thursday, July 31 through August 4, 1994, at the Seattle Convention Center. Exact locations and dates for the workshops will be determined in early February. The AAAI-94 Workshop Series includes twenty-one workshops covering a wide range of artificial intelligence topics. Participation at these workshops is by invitation from the workshop organizers. Most workshops are one day long; exceptions are noted in the individual workshop descriptions. Each workshop is limited to approximately thirty to fifty participants. Workshop attendance is free for those registering for the AAAI-94 or IAAI-94. There is a $125 registration fee for those attendees who do not register for AAAI-94 or IAAI-94. All workshop attendees must preregister for the workshops or main conference. Workshop working notes will be distributed onsite for participants only. Submission Requirements Submission requirements vary with each workshop, and are listed under each title. Submissions for all workshops are due March 18, 1994. Workshop organizers will notify submitters of acceptance by April 8, 1994. Camera ready copy is due back to workshop organizers by April 29, 1994. Please mail your submission directly to the chair of the individual workshop. Do not mail submissions to AAAI. For further information about a workshop, please contact the chair of that workshop. AAAI-94 Workshop Chair Don Perlis, University of Maryland AI and Systems Engineering Systems engineering (SE) is the iterative process of top-down design and bottom up synthesis and analysis, development, operation, maintenance and enhancement of a real-world system that satisfies, in an optimal manner, the full range of the requirements for the product or system. It encompasses the entire life-cycle of a system, from initial need perception, to requirements formulation, to partitioning into subsystems, to design, testing, and integration of subsystems, documentation, fielding, maintenance, and system enhancements and requirements modification. Because of the increasing complexity of human-made systems, the integrated approach of systems engineering is one possible solution to the creation of successful, globally competitive products. Because of its complexity, interdisciplinary nature and reliance on human expertise and experience, SE can benefit from techniques and models developed in AI. Knowledge representation, expert systems, case-based reasoning, constraint-based reasoning, truth maintenance, qualitative modeling, and design theory are some of the techniques that could be used to help systems engineers. The intent of this one-day workshop is to bring together SE and AI researchers and practitioners to discuss on-going and potential research and development activities. We encourage paper submissions presenting promising ongoing research or developing applications as well as papers presenting mature research and applications. Topics - Modeling of large, heterogeneous systems - Systems level process modeling - Systems level requirements acquisition, representation and verification - Systems level design representation and verification - Systems level integration and testing - System maintenance and change management - Successful and unsuccessful applications of AI to SE - Panel discussions concerning future applications of AI to SE Attendance Practicing systems engineers and researchers in SE and AI are encouraged to attend. The attendance will be limited to approximately 40 people with an even mix from industry and academia. Format Presentations will be brief (10-15 minutes maximum), and will be followed by a panel discussion between the authors and the audience, directed by a panel leader. We intend to split the available time evenly between paper presentations and panel discussion. Workshop notes will be distributed to all participants. Submission Requirements If you wish to present, submit four copies of an extended abstract (three to five pages) using twelve point font and 8.5" x 11" page size. Abstracts may be submitted in electronic (Latex or PostScript) or hard copy form. Final papers are limited to a maximum of ten pages in length using twelve point font and 8.5''x 11'' page size, including references and figures. If you only wish to attend and participate in discussions, send a one-page position paper describing your interests. Position papers may be submitted in electronic (text, Latex, or PostScript) or hard copy form. Submit to Workshop Chairperson: Perry Alexander ECE Dept, ML #30 The University of Cincinnati Cincinnati, OH 45221-0030 Perry.Alexander@UC.Edu 513-556-4762 513-556-7326 (fax) Organizing Committee Costas Tsatsoulis, Dept. of Electrical Engineering and Computer Science, The University of Kansas (tsatsoul@kuhub.cc.ukans.edu) and Julian C. Holtzman, Director, Center for Excellence in Computer Aided Systems Engineering, The University of Kansas (J_Holtzman@qm-gateway.cecase.ukans.edu). AI in Agriculture and Natural Resource Management This workshop will cover innovative research in the application of AI to the areas of natural and agricultural resource management. The scope of the problem domain includes the management and utilization of agroecosystems (i.e., farms) and natural ecosystems (e.g., forests, watersheds, recreational areas). Rule-based expert systems have become common in these domains. It is apparent, however, that this paradigm alone is inadequate for many of the problems facing resource managers. Natural and agricultural ecosystems are extremely complex. Often, management is toward multiple, and at times conflicting, objectives, and the knowledge required to do a creditable management job tends to be multi-disciplinary. In the face of these problems, researchers are investigating the application of more advanced AI techniques. In addition, a growing trend is toward the integration of multiple software technologies (e.g., simulation modeling, geographic information and database management systems) with AI methodologies. This workshop will provide a forum for the discussion of these issues, and a venue for interaction between researchers in the field. Format This two-day workshop format will inlude 10-15 presentations, plus possible discussion periods. Workshop participation will be limited to approximately 50 individuals. Persons interested in making a presentation should submit an extended abstract (no more than 2 pages) of the proposed talk. Special consideration will be given to subjects that move beyond the application of rule-based techniques. Topics Appropriate topics include: - Model-based reasoning in biotic systems - Uncertainty in resource management - Reasoning with spatial knowledge - Case-based reasoning - Neural networks - Planning - Constructing explanations for observed patterns in nature (abduction) - Multiple paradigm integration issues - Philosophical issues pertaining to machine intelligence and the management of biotic systems. Submissions and Attendance Participants who do not want to present should submit a short abstract (a page or less) describing their research or interest in the subject area. Submissions should be sent, in hard-copy form, to: Richard L. Olson USDA-ARS, P.O. Box 5367 Miss. State, MS 39762-5367 601/324-4367 rolson@asrr.arsusda.gov Organizing Committee Richard Olson, Mississippi State University; Douglas K. Loh, Texas A&M University; John Roach, Virginia Polytechnic Institute and State University; Nicholas Stone, Virginia Polytechnic Institute and State University. AI in Business Increasingly, AI is moving out of the lab and into business organizations. As a result, political, sociamanagerial and technological issues are in influencing the introduction of systems into organizational environments. This results in some unique opportunities and concerns. First, approaches that work in the lab do not always work in practice. As a result, it is important to examine the use of different methodological approaches to different contexts. Second, with the movement of AI into business settings, there is often the need to understand the influence of the business organization on the use of AI and the impact of AI on the organization. Third, other issues such as the integration of AI into existing technology usage are also important. For example, implementation issues must address the integration of AI with existing database systems and with competitive (and complementary) decision making approaches, such as, decision analysis and operations research. Fourth, economic impact becomes a critical concern. Cost benefit analysis and the diffusion of AI become important since ultimately the firm is an economics-based organization. Topics - Applications: New and unique applications of AI in business. - Organizational Issues: Organizational impact of AI in business; worker displacement; management power shifts; and organizational structure issues. - Economic Issues: Economics of AI; creating value with AI; cost benefit analysis of AI; economic diffusion of AI cognitive models: audi tor judgment; bank loan judgment; credit judgment. - Integration Issues: Integrating AI and OR; integrating AI into conventi onal information systems; integration of neural nets and expert systems. - Methods: Model-based financial reasoning; qualitative reaso ning in business models; case-based reasoning in business; multiple agent models. Format The one-day workshop will consist of paper presentations, panels, discussions and system demonstrations. Attendance Academic, practitioner, and international participation is encouraged. Participants will be chosen based on materials submitted. Submission Requirements Authors should submit a technical paper of 10-20 pages, double spaced; an extended abstract of a research project or application of at least three pages; or a summary of previous work. Three hardcopies should be sent to Dan O'Leary 3660 Trousdale Parkway University of Southern California Los Angeles, CA 90089-1421 213/740-4856 email: oleary@rcf.usc.edu Organizing Committee Dan O'Leary, (chair); John Bailo, (cochair); Arnold Jolles, James Rey, Mallory Selfridge, Paul Watkins, and Dan Pirone. AI in Intelligent Vehicle Highway Systems A major goal of IVHS is to develop a surface transportation system that offers increased performance in transporting people and goods and improved safety while reducing traffic congestion, accidents, and pollution. The federal government authorized more than $200 million for IVHS R&D and testing for 1993 alone. However, federal funding is only a portion of the overall IVHS market, which is expected to be a multi-billion dollar market. Although many projects have been operational or under extensive testing in the US, European countries, and Japan, there still remain many difficult problems in realizing the goal. The AI community can play a major role in IVHS, as a FHWA representative reminded us during the past year's workshop. The major aim of the 1994 one-day workshop will be to bring together researchers, engineers, and government officials from both IVHS and AI communities. A second aim will be to exchange ideas and approaches toward actually solving some of the IVHS problems using AI. We will focus on technical issues, discussing IVHS problems that have good use of AI, especially in the areas of advanced traffic management systems (ATMS), advanced traveler information systems (ATIS), and advanced vehicle control systems (AVCS). Those will include, but not limited to: incident detection and management; real-time, adaptive signal control and simulation; intelligent sensor systems; optimal route selection algorithms; intelligent signal timing plan selection systems; intelligent decision support systems for logstics; intelligent user interface; and dri er behaviorprediction systems. Attendance Key people in IVHS will be invited to give addresses. Papers from the AI community are solicited that treat with IVHS problems. Invited participants will include representatives from the Federal Highway Administration, state and local departments of transportation, Intelligent Vehicle Highway Society of America, Transportation Research Board, various universities, research organizations, and commercial companies. Submissions Send abstracts (3-5 pages, single spaced, hard copy, size 12, with your address, telephone number, and email address) to the workshop chair: Yukiko Sekine Video Active Technology, Inc. 3053 Braxton Wood Court Fairfax, VA 22031 All accepted papers will be included in the workshop notes, which could later be published by AAAI. For any other communication, please send email to coorganizer Dr. Gang Len Chang at gang@eng.umd.edu. Organizing Committee Yukiko Sekine, (chair), Video Active Technology, Inc.; Gang Len Chang, University of Maryland. AI Technologies for Environmental Applications This workshop, cosponsored by NASA Ames Research Center, brings together two diverse groups of people with the aim of understanding the potential and problems of applying AI technologies to environmental applications: - Researchers and scientists whose goal is to increase our understanding of physical, chemical and biological processes - particularly researchers studying atmospheric, climatic, ecological oceanic, and solid-earth processes - as well as environmental engineers concerned with problems regarding pollution control, natural disaster planning, and hazardous materials management. - AI researchers and practitioners whose goal is to develop and engineer methods for automation and information processing required by environmental applications; for example, novel methods for acquiring sensed data (e.g., Antarctic robotic explorers), systems that assist in processing, archiving, and distribution of increasingly diverse and voluminous sensed data (e.g., as in earth observing systems), modelling earth processes, and planning in data analysis or hazardous waste disposal. The workshop provides an important and timely forum for participating researchers, scientists, and engineers to explore the novel problems environmental studies present, and to examine the fruits of traditional and non-traditional AI systems as applied to environmental applications. The objective of the workshop is to foster discussion, bringing together the experience base of environmental scientists and engineers with the information handling experience of AI theorists and practitioners. The workshop will focus on two topics: AI in environmental engineering (pollution control, natural disaster planning, hazardous materials management); and AI in environmental sciences (hydrological, oceanic and ecological systems studies, earth and climate process prediction, and upper atmosphere studies). Papers on both applications of existing AI techniques, as well as contributions to AI research, are solicited. Papers clarifying the information science problems in environmental science and engineering are especially welcome. Suggested Topics - Interactive data exploration and discovery - Data and knowledge visualization - Archival and retrieval methodologies - Data integration for environmental monitoring applications - Open problems in information processing for environmental studies Format The workshop is planned for 2 days with presentations of papers, invited talks, open discussions and posters; ample time will be devoted to discussions. The workshop is limited to 50 participants. Participants will be chosen by program committee on basis of submitted materials or extensive relevant research work or publications and willingness to participate in discussion. Submission Requirements Participants are invited to submit 5 hard copies of a technical paper (not to exceed 10 pages, double spaced), or a paper appropriate for poster session. Technical papers should include a cover page containing title, authors' names, U.S. mail address, email address, and a brief abstract. The submitted papers should not have been previously published. Participants with relevant research experience who wish to attend should provide details of their experience/current research rojects. Submit to: Cindy Mason AI Research Branch, MS 269-2 NASA Ames Research Center Moffett Field, CA 94035-1000 415/604-0305 415/604-3594 (fax) mason@ptolemy.arc.nasa.gov Organizing Committee Ron Gore and Ted Metzler, LB & M Associates; Cindy Mason, Rich Keller, and Amy Lansky, NASA Ames Research Center; Roger King, Mississippi State University; Farid Dowla, Lawrence Livermore National Laboratory; Ed Gillis, Automotive Systems Laboratory. Artificial Intelligence, Artificial Life, and Entertainment It is increasingly recognized that the entertainment industry will be one of the major industries in which the power of computing plays a key role. This is particularly evident when one observes the intense pace of collaborations, mergers, and corporate purchases at the boundary between entertainment and computing. The popular press has referred to this as "the merger of Hollywood and Silicon Valley". For this merger to succeed in the long term, machines must become competent in entertainment industry tasks presently performed by humans. This is very much the domain of AI research and development. Thus, this workshop focuses on the applications of artificial intelligence and related technologies to entertainment. The purpose of the one-day workshop is that by broadly soliciting papers in the area, which has not been studied by much of the AI community in the past, we expect to draw an overall picture of AI opportunities in the entertainment industry. Also, we expect that information will be exchanged to influence AI research directions and to facilitate active resea rch n AI for entertainment. Topics We welcome papers that clearly demonstrate use (including both actual use and ideas and proposals) of AI and related technologies (such as artificial life, neural networks, robotics, and genetic algorithms) in all areas of entertainment, including: - Film (movie, video, etc) production - Computer graphics and animation - Interactive fiction, simulated worlds, role playing games - Video games - Network-based games - Virtual reality - Autonomous systems and agents - Interactive media - Music, sound, and speech - Drama and story-telling - Robotics, animatronics - Theme park applications Format AAAI-94 will include several activities relevant to the topics of this workshop. We expect the conference to attract a variety of people working in the area, and intend the workshop to provide an opportunity for many of them to meet and discuss plans for further research and development. Submissions Send two copies of an extended abstract, no longer than 8 pages, to both workshop cochairs. Hiroaki Kitano Sony Computer Science Laboratory 3-14-13, Higashi-Gotanda Shinagawa Tokyo, 141 Japan (+81) 3-5448-4273 fax kitano@csl.sony.co.jp Joseph Bates Carnegie Mellon University School of Computer Science 5000 Forbes Ave. Pittsburgh, PA 15213 U.S.A. 412-681-5739 (fax) joseph.bates@cs.cmu.edu Artificial Intelligence in Business Process Reengineering Business process reengineering (BPR) achieves order of magnitude increases in performance through a complete redesign of business processes. This workshop will focus on the roles of AI in the design phase of business process reengineering, encompassing recent research on AI tools for assisting in process design. Topics Promising areas for AI in supporting BPR include supporting process modeling, generating innovative process models, and combining of qualitative and quantitative simulations. At least three related approaches to modeling are currently being explored. The first is knowledge-based simulation, in which the objective is to produce a quantitative or stochastic simulation of a business process. AI technology provides the knowledge-based environment in which designers can specify the model in terms of components and connections, using varying levels of structural and type hierarchies, to construct models. Knowledge-based simulation has demonstrated its value in commercial tools. Symbolic evaluation is a second alternative which anayzes a causal model of a process in terms of the behavior of its constituent elements in order to characterize its global behavior. Third, qualitative modeling and analysis of processes is useful for modeling when the data needed for quantitative or stochastic analysis is not available. This approach is illustrated by systems that perform qualitative analysis of financial entities. Each of these techniques, however, has its limitations: the limited inferential power of purely qualitative reasoning is well documented, symbolic evaluation is often intractable unless the form of the model is carefully controlled, and knowledge-based simulation ultimately relies on simulation techniques that presume the availability of quantitative data that may be simply unavailable. Research efforts in all of these areas have in common the need to balance the difficulty of acquiring and constructing the process model against the need to produce reliable and informative results from analysis. Another dimension of modeling concerns arises from the fact that Barly all BPR efforts require collaborative effort across orga izational bondaries, and both modeling an enterprise as is and to be result an large andcomplex models, forcing issues of scalability and knowledge ma agemenato be addressed. Format The workshop will be a half day and is intended to stimulate interaction between the AI research community and BPR practitioners. Invited authors will be given a substantial time slot, followed by a short time slot for a respondent with a prepared commentary. Attendance and Submissions Attendees may either submit three copies of a technical abstract of up to five pages, or a shorter position paper. Invitations to make presentations will go to submissions based on relevance to the workshop topic, technical contribution, and clarity of presentation. Demonstrations of live programs in support of technical presentations will be strongly encouraged. Some attendees will be asked to serve as respondents for accepted presentations. Fax submissions are discouraged; hardcopy is acceptable; E-mail is preferred. Authors of accepted papers must subsequently provide camera ready c opies. Submit to: Walter Hamscher Price WaTrhouse Technology Centre 68 Willow Road Menlo Park, CA 94025 415/688-6669 415/617-7869 (fax) Walter_Hamscher@notes.pw.com Organizing Committee Walter Hamscher, cochair, Price Waterhouse; Pramod Jain, cochair, Andersen Consulting; Robert Friedenberg, Inference Corporation; Gerry Williams, Andersen Consulting; Dorothy Yu, Coopers and Lybrand. Case-Based Reasoning Several workshops have encouraged theoretical proposals on case-based reasoning (CBR). This workshop focuses instead on systematic evaluation of CBR theories, models, systems, and system components (e.g., retrieval, elaboration, adaptation, and learning). Our goal is to increase awareness of how to conduct such evaluations so that they yield useful insights for the design of subsequent systems. Topics Topics include the evaluation of the cognitive plausibility of CBR models of human cognition; comparisons among different CBR systems or components, or between CBR and other approaches; descriptions of CBR applications with emphasis on lessons learned from user feedback; evaluations of CBR components in systems that employ large case bases and abundant domain-specific knowledge; mathematical analyses; and computational benefits of cognitively plausible CBR models. Researchers and practitioners conducting related work from fields not always associated with CBR are encouraged to participate. We hope to accumulate and disseminate knowledge gained from studying CBRlike algorithms in several fields (e.g., memory-based reasoning, k-nearest neighbor, etc), thus identifying problem issues and reducing replications of previous work. Format This two-day workshop will include invited talks, paper presentations, two interactive panel discussions, and a poster session. The invited talks will include summaries of the performance of currently fielded CBR systems as well as CBR-related contributions in areas not traditionally associated with CBR. The first panel will focus on the utility and limitations of evaluations. The first day will end with the poster session. The second day will include a panel on a controversial issue (to be determined), critiques of the field, its direction, and of the workshop's presentations, and a summary discussion. Attendence is limited to 50 invitees. Additional invitations will be made as space permits to those who submit written requests. Submission Requirements Five copies of each paper should be submitted in hard copy form. The cover page should contain a title, authors' names, mailing address, email addresses, telephone numbers, and a brief abstract. Papers should not exceed 12 single-spaced pages including figures and bibliography. Working notes containing the accepted papers will be distributed, along with a possible AAAI technical port. Please send submissions to: David W. Aha NCARAI Naval Research Laboratory Code 5514, 4555 Overlook Ave, SW Washington, D.C. 20375 USA 202/767-9006 202/767-3172 (fax) aha@aic.nrl.navy.mil Organizing Committee David W. Aha; Christopher G. Atkeson, MIT, cga@ai.mit.edu; Ray Bareiss, Northwestern University, bareiss@ils.nwu.edu; L. Karl Branting, University of Wyoming, karl@eolus.uwyo.edu; Ashwin Ram, Georgia Institute of Technology, ashwin@pravda.cc.gatech. edu; Evangelos Simoudis, Lockheed AI Center, simoudis@aic.lockheed.com; Manuela Veloso, CMU, mmv@cs.cmu.edu. Comparative Analysis of AI Planning Systems The purpose of this workshop is to categorize the many different approaches to AI planning, to begin to understand the relative strengths and weaknesses of these competing approaches, and to understand the specific ways in which these strengths and weaknesses relate to features of realistic application domains. An important aspect of understanding applications of planners will be to categorize the tasks that can be addressed, and the capabilities of the agents executing the plans. The workshop will focus on methods for the description, comparison and evaluation of existing planning techniques. Papers are solicited that address any of the following issues: - How can an application of a planner to a problem be analyze d and evaluated? - How can one predict the class of problems to which a planner will be applied successfully? - What are the various components of problem complexity a nd how will planners scale up as complexity increases? - What experiments can be run to answer these questions? - Is the application of planners to real problems being held b ack not by the planning technology per se, but by supporting technology that needs to be integrated with a planner? While developing the methodology of evaluation is the goal, papers analyzing or evaluating specific problems and planning systems are also welcome, provided they exhibit a good methodology for evaluation on complex problems. Papers that simply describe the use of a single system on a specific application are not appropriate for this workshop. Schedule This will be a one-day workshop. The morning and part of the afternoon will be devoted to presentation of papers. That will be followed by a panel and open discussion aimed at producing a working paper to establish a list of technical features included in AI planners, a related list of application features, and to begin discussions on how these are being evaluated and tested by the participants at the workshop. Submissions Submissions should be made to the chair of the organizing committee, either in hardcopy or by email. Electronic submissions are strongly preferred. Mail four hardcopies or email a standard postcript file, or a latex file that uns on vani la latex. Submit to: David E. Wilkins Artif icial Intelligence Cente r SRI Internationa l EJ227 333 Ravensw ood Ave. Menlo Park, CA 94025 wilkins@ai.sri.com Organizing Committee David E. Wilkins, (chair), SRI International, wilkins@ai.sri.com; Martha E. Pollack, University of Pittsburgh, pollack@cs.pitt.edu; Matthew L. Ginsberg, University of Oregon, ginsberg@cs.uoregon.edu; Austin Tate, AIAI, University of Edinburgh, A.Tate@ed.ac.uk. Computational Dialectics Dialectic is an idea that simply will not disappar. It is the idea of structured linguistic interactions proceeding according tBa largely adversarial protocol. Beginning wi h the ancients, dialecticappears to many to be synonymous with rationa lity. Today, computation iforms the study and use of such structured dia ogues. Substantial conaibutions are now possible from artificial intelligence researchers. Computational dialectics is meant to describe an area of activity in AI, which considers the language and protocol of systems that mediate the flow of messages between agents constructing judgement, agreement, or other social choice, to recognize or achieve an outcome in a fair and effective way. The study of communal standards for acquiring knowledge and making decisions has always been interesting as a basis for computational models of deliberation. The study of argument and negotiation in naturally occurring dialogues has been the focus of work in language processing and explanation generation. The study of analogy and case-based reasoning has produced dialectical models that have been successfully applied in the domain of conflict resolution, negotiation and legal argument. The implementation of nonmonotonic reasoning systems and the semantics of logic programming has also converged on dialectic. Philosophers' formalization of defeasible reasoning has produced new understanding of why dialectic is not merely roundabout proof. Researchers of HCI and CSCW have had occasion to study how the interplay of argument, counterargument, and rebuttal affects design, clarifies presentation, and improves interaction. The rediscovery of pro and con recalls AI's early foundations upon max and min. Goals The primary goal of this one-day workshop is to identify areas where computationally motivated language games can contribute new scholarship or interesting software technology. Historical and rhetorical aspects of dialectic will be considered only to the extent that they advance the models of computer scientists. We are interested more in what computer scientists will have to say to the dialecticians than vice versa. Format Efforts will be made to involve established leaders in related fields, and to make the best use of the contributions. The format will include both presentations and open discussions, and of course, debate. Duration will depend on the field of submissions. Plans for future publications are being developed. Topics - Standards of correctness, effectiveness, and fairness of protocols. - Formal language games for particular kinds of tasks, such as cooperation, negotiation, argumentation, and conflict resolution. - Toolkits for implementing systems that embody dialectical ideas. - Work on logics of dialogue, defeasi ble reasoning, logic programming, uncertain reasoning, case-based r easoning, legal reasoning, planning, search, or social choice that is aimed at modeling dialectical processes. - Applications of formal languag e games of this kind, in fields such as cooperative design, distributed AI, telecommunications, law, and business. Submissions Two kinds of submissions can be made for participation. 1). An extended abstract of a paper can be submitted for possible presentation; or 2). A brief statement of interest and background can be sent for consideration as a participant. Preference will be made to those who can propose computational frameworks for modeling argument and negotiation or otherwise shed light on the complexities of dialectical inquiry. Please include a telephone number and an email address. Submissions can be made to any of the committee members and may be electronic. The preferred European address is: Thomas Gordon GMD Postfach 1240 1 Sankt Augustin Bonn, Germany thomas@gmdzi.gmd.de The preferred US address is: R. P. Loui Box 1045 Washington University St. Louis, MO 63130 loui@ai.wustl.edu Organizing Committee Thomas Gordon (cochair), GMD; R. P. Loui (cochair), Washington University; Johanna Moore, University of Pittsburgh, jmoore@ cs.pitt.edu; Katia Sycara, Carnegie Mellon University, sycara@cs.cmu.edu. Device Function The explicit representation of device function, and its associated recognition, interpretation, evaluation, application, and integration has attracted increased interest due to its ability to address large scale problems on many abstraction levels without loss of resolution. Device function organizes the knowledge associated with, and provides access to, both low- level device behavior and high-level device use in problem solving, and so has been applied in such disparate fields as education, psychology, medical diagnosis, engineering design and diagnosis, and computer science. Objectives - Resolve or address problems a rising from the different research domains and paradigms which comprise the community - Construct coherent research approaches for addressing common problems - Plot the course of the field of function-based representation and reasoning Topics Terminology/Representation: The function-based reasoning community generally agrees on the existence of five types/levels of knowledge associated with the representation of and reasoning with device function: - Structural--structural characteristics and device appearance, where applicable - Behavioral--how function is achieved - Functional--observed device input and output - Intentional--a device's design intent or use - Experiential--a device's interpretation/evaluation in context There are differing terms for these categories, and differing approaches to how these categories should be: related to one another, combined, and implemented. Most significant is still the definition of function itself, and whether intention should specifically be associated with the representation of function. The enthusiastic discussion over terminology and representation which was begun at the 1993 AAAI Reasoning about Function workshop will be continued at the forthcoming workshop. Reasoning: What tasks/domains are particularly suited to reasoning with functional device models? What processes are involved in exploiting knowledge of device function during reasoning? How can reasoning about structure, behavior, function, use, and experience be integrated into a coherent system? Applications: An examination of implemented systems, representation and reasoning techniques used, evaluation of the system, and lessons learned from the experience. Format The half-day workshop will consist of moderated presentations and discussions. Where appropriate, participants will be invited to display posters describing their work. Separate sessions will be devoted to terminology and representation issues, reasoning-specific issues, and applications. Participation will be limited to approximately 35 invited people. Submission Requirements Those who wish to attend the workshop should submit a 1-2 page research summary including: a list of relevant publications, regular and email address (where possible), and appropriate voice and fax phone numbers. Those who wish to present their work at the workshop should also submit a short paper (6-8 pages). Specify if the work has been published or submitted for consideration elsewhere, and, if so, the journal or conference. Unpublished work is preferred for presentation. Electronic submissions are strongly preferred, especially in LaTeX source or PostScript formats. If hardcopy is necessary, please submit four copies. Send email to the workshop coordinator for information. All submissio S will be reviewed by the organizing committee. Submit to: Jack Hodges Assistant Professor Computer Science Department San Francisco State University 1600 Holloway San Francisco, CA 94132 415/338-2335 415/338-6136 (fax) hodges@huckleberry.sfsu.edu Organizing Committee Dean Allemang, Swiss Federal Institute of Technology, allemang@lia.di.epfl.ch; David Franke, Trilogy Development Group, franke@trilogy.com; Jack Hodges, San Francisco State University, hodges@huckleberry.sfsu.edu; Amruth N. Kumar, SUNY Buffalo, amruth@cs.buffalo. edu; James K. McDowell, Michigan State University, mcdowelj@pleiades. cps.msu.edu; Chris Price, University of Wales, cjp@aber.ac. uk; Jon Sticklen, Michigan State University, sticklen@cps.msu.edu; Shambhu J. Upadhyaya, SUNY Buffalo, shambhu@ cs.buffalo.edu. Experimental Evaluation of Reasoning and Search Methods There is considerable current interest in the experimental evaluation of reasoning and search methods. The evolving body of experimental work has already begun to revitalize work in reasoning and search, and has attracted interest (and respect) beyond the normal audience for AI results. Experimental evaluations of reasoning and search methods allow us to identify properties of algorithms and problems that cannot yet be analyzed rigorously. As a concrete example, consider the threshold phenomenon in 3SAT. (In randomly generated 3SAT instances, as the number of clauses per variable is increased there is a sharp transition from most instances being satisfiable to most instances being unsatisfiable.) The location of this threshold has now been determined very precisely, within a few percent accuracy, using experimental methods. The best theoretical results give a lower- and upper-bound on the threshold value. Using these bounds, one can predict the actual location of the threshold with only about 30 percent accuracy. For generating interesting test instances for the evaluation of satisfiability procedures, we therefore have to rely on the experimentally determined threshold value. Similarly, a rigorous analysis of the performance of many satisfiability procedures is well beyond the state-of- the-art in algorithmic analysis. Experimental study of those methods is currently our only option. Another reason for experimental studies of algorithms is the need for obtaining average-case results. It is generally agreed that standard worst- case analysis can lead to an overly pessimistic evaluation of algorithms. The obvious alternative is to do some form of average-case analysis. An average-case analysis requires, however, a precise characterization of the distribution over the input instances as they occur in practice. Such a characterization is often not available. Again, experimental work offers an alternative: assuming that one has access to a reasonable source of instances, one can study empirically the performance of algorithms running on those instances. Of central importance in the evaluation of experimental work are the interpretation of the experimental data and the reliability of that interpretation. These issues will be the focus of our workshop. Ideally, our discussions will lead to a set of standards and possibly benchmarks for future experimental work in the area of reasoning and search. Format The one-day workshop format will be fairly informal. We expect to divide our time roughly evenly between presentations and discussion. The workshop will center around the following topics: - New experimental results on reasoning and search - Proposals for benchmark problem classes - Position papers on experimental design and evaluation Submissions Prospective participants should submit a short summary of their recent research, a position paper, or a technical paper on experimental results or benchmark problems. Research summaries and position papers should not exceed 4 pages. Technical papers should not exceed 8 pages. Four copies of each submission should be sent to: James M. Crawford CIRL 1600 Millrace, Suite 108 Eugene, OR 97403-1269 or jc@cs.uoregon.edu (Postscript [preferred] or self-contained LaTex). Please feel free to send questions by email to any of the committee members. Organizing Committee James Crawford (cochair), CIRL, University of Oregon, jc@cs.uoregon.edu; Bart Selman (cochair), AT&T Bell Laboratories, selman@research.att.com; David McAllester, MIT AI Lab, dam@ai.mit.edu; Mark Stickel, SRI International, stickel@ai.sri.com; Peter Cheeseman, NASA Ames Res. Center, cheeseman@pluto.arc.nasa.gov. Indexing and Reuse in Multimedia Systems Multimedia systems for documentation, training, entertainment, or news use a variety of indexing schemes to annotate and access media for further use. As these systems grow, issues of how to represent, acquire, and refine indexing knowledge for effective information access and reuse become crucial. Yet, analysis of the indexing task and research on indexing methods and t oB for multimedia are just beginning to emerge. Because automated parsing techniques for time-based and visual media are currently in the early stages of development, systems for multimedia material must often operate with partial or no representations of their information content. However, these systems can still produce information that is useful for the end-user. Such hybrid human-machine representation and communication provides opportunities to investigate interactive methods for index acquisition and refinement, which may complement and even improve automatic parsing techniques. Topics This workshop focuses on methods and tools for indexing, searching, and reusing information in multimedia systems. We would like to bring together researchers in knowledge acquisition, case-based reasoning, multimedia system design, human-computer interaction, speech and visual perception, and other relevant disciplines. We also encourage contributions from video archivists, videographers, editors, or sound designers who may not have an AI background, but have experience in representing and indexing multiple media. We welcome contributions in the following areas: Indexing tools: - Knowledge acquisition or ma chine learning techniques to acquire or refine indexing knowledge. Incr emental refinement of semiformal representations. Incremental generation of hypermedia links, etc. - Integration of autom ated parsing techniques that process signals or text with conceptual (semantic) indexing techniques. - Analysis of the typ es of interactions with humans that a system can use to reorganize its memory. Index representations and refinement for reuse: - Index repre sentations and reuse for different purposes and classes of users. - Completing, generalizing, adding context to indexing schemes. - Index rep resentations and acquisition which address the media-specific properties of time-based and visual media. - Com parison between different indexing schemes: domain-dependent vs. domain -independent, semantic vs. episodic, absolute (information content) vs. relative (links between information fragments as in hypermedia). - Em sirical evaluation of information organization and reuse in multimedia systems. The practice of indexing: - Case studies and analysis of indexing practice which deal with pragmatic questions: Who are the indexers? How deep must their understanding b e of the content of the indexed information? When is indexing performed, in real-time during the data generation or after the fact? Format The duration of the workshop will be one day and will consist of at most fifty (50) participants. To leave time for discussion only a subset of the selected papers will be presented. Each session will comprise: presentations by authors of selected papers; a short analysis or critique of the papers presented by the session chair; and a discussion with the authors and the workshop participants. In addition we will have a panel and one or two invited speakers. Submission Please send four copies of a five-to-twelve-page paper to the workshop chair, Catherine Baudin. Those who would like to attend without submitting a paper should send a one to two page description of their relevant research interests. Presenters are encouraged to bring live demos and/or videos of their work. Organizers intend to pursue publication of a selection of the accepted papers. Catherine Baudin (chair) AI Research Branch NASA Ames Research CenterMS 269/2 Moffett Field, CA 94035. USA. 415/604 4745 415/604 3594 (fax) baudin@ptolemy.arc.nasa.gov Organizing Committee Catherine Baudin (chair), NASA Ames Research Center; Marc Davis, (cochair), MIT Media Laboratory and Interval Research Corp., davis@interval.com; Smadar Kedar, (cochair), ILS, Northwestern University, kedar@ils.nwu.edu; Daniel M. Russell, (cochair), Apple Computer Inc.,dmrussel@taurus.apple.com; Ray Bareiss, ILS, Northwestern University; Guy Boy, EURISCO; Tom Gruber, Stanford University; Ken Haase, MIT Media Lab; Doug Lenat, MCC; Nathalie Mathe, NASA Ames Research Center; Scott Minneman, Xerox PARC; Dick Osgood, ILS, Northwestern University; Jim Spohrer, Apple Computer Inc.; Meg Withgott, Interval Research Corp. Integration of Natural Language and Speech Processing This two-day workshop will focus on research involved in the integration of Natural Language Processing (NLP) and Speech Processing (SP). The aim here is to bring to the AI community results being presented at computational linguistics (e.g. COLING/ACL), and speech conferences (e.g. ICASSP, ICSLP). Although there has been much progress in developing theories, models and systems in the areas of NLP and SP we have just started to see progress on integrating these two subareas of AI. Most success has been with speech synthesis and less with speech understanding. However, there are still a number of important questions to answer about the integration of speech and language processing. How is intentional information best gleaned from speech input? How does one cope with situations where there are multiple speakers in a dialogue with multiple intentions? What corpora (e.g. DARPA ATIS corpora, MAP-TASK corpus from Edinburgh) exist for integrated data on speech and language? How does discourse understanding occur in multi-speaker situations with noise? How does prosodic information help NLP systems? Topics Themes for integrated NLP/SP include theoretical issues; systems exhibiting; and intelligent multimedia Issues for integrated NLP/SP include common representations; how NLP helps SP and vice-versa; what integration buys us; symbolic versus connectionist models; varieties of communication between NLP/SP processors; designs; tool; corpora; testing; and possible applications Workshop Format Our intention is to have as much discussion as possible during the workshop and to stress panel sessions and discussion as well as having formal paper presentations. We will also organize a number of presentations on site descriptions of ongoing work on NLP + SP. There may be a number of invited speakers. The first day will feature theory and modelling for integrated NLP and SP. Day two will feature systems for integrated NLP/SP, and intelligent multimedia. We hope to have an attendance between 25-50 people at the workshop. Workshop notes will be published by AAAI; further publication may be pursued if there is interest. Submission Requirements Papers of not more than 8 pages should be submitted by electronic mail to Paul McKevitt. Preferred format is two columns with 3/4 inch margins all round. Papers must be printed to 8 1/2" x 11" size. Double sided printing is encouraged. If you cannot submit your paper by e-mail please submit three copies by airmail: Paul Mc Kevitt, (chair) Department of Computer Science Regent Court, University of Sheffield 211 Portobello Street GB- S1 4DP, Sheffield England, UK p.mckevitt@dcs.shef.ac.uk +44 742 825572 (office) +44 742 825590 (secretary) +44 742 780972 (fax) Organizing Committee Ole Bernsen, Martin Cooke, Noel Sharkey, Eiichiro Sumita, Walther V.Hahn, Yorick Wilks, Wolfgang Wahlster, Sheryl R. Young. Integration of Natural Language and Vision Processing There has been a recent move towards considering the integration of perception sources in artificial intelligence. It is not clear why there has not already been much activity in integrating natural language processing (NLP) and vision processing (VP). Is it because of the long-time reductionist trend in science up until the recent emphasis on chaos theory, non-linear systems, and emergent behaviour? Or, is it because the people who have tended to work on NLP tend to be in other departments, or of a different ilk, to those who have worked on VP? This two-day workshop is of particular interest at this time because research in NLP and VP have advanced to the stage that they can each benefit from integrated approaches. Also, such integration is important as people in NLP and VP can gain insight from each others' work. Topics Themes for inte grated NLP/VP: - Theoretical issues - Systems exhibiting - Intelligent multimedia Issues for integrated NLP/VP: - Common representations - How does NLP help VP and vice-versa? - What does integration buy us? - Symbolic versus connectionist models - Varieties of communication between NLP/VP processors - Designs - Tools - Possible applications Format Our intention is to have as much discussion as possible during the workshop and to stress panel sessions and discussion as well as having formal paper presentations. We will also organize a number of presentations on site descriptions of ongoing work on NLP + VP. There may be a number of invited speakers. We hope to have an attendance between 25-50 people at the workshop. Day One: Theory and modelling for integrated NLP and VP. Day Two: Systems for integrated NLP/VP, and intelligent multimedia. Workshop notes will be published by AAAI. If there is sufficient interest we will publish a book on the workshop with AAAI Press. Submission Requirements Papers of not more than 8 pages should be submitted by electronic mail to Paul McKevitt. Preferred format is two columns with 3/4 " margins all round. Papers must be printed to 8 1/2" x 11" size. Double sided printing is encouraged. If you cannot submit your paper by e-mail please submit three copies by airmail. Paul Mc Kevitt, (chair) Department of Computer Science Regent Court, University of Sheffield 211 Portobello Street GB- S1 4DP, Sheffield, England, UK p.mckevitt@dcs.shef.ac.uk +44 742 825572 (office) +44 742 825590 (secretary) +44 742 780972 (fax) Organizing Committee Jerry Feldman, ICSI; John Frisby, Sheffield, England; Eduard Hovy, USC ISI; Mark Maybury, MITRE; Ryuichi Oka, RWC; Terry Regier, ICSI; Roger Schank ILS; Oliviero Stock, IRST; Wolfgang Wahlster, DFKI; Yorick Wilks, Sheffield, England. KDD-94: Knowledge Discovery in Databases Knowledge discovery in databases (KDD) is an area of common interest for researchers in machine learning, machine discovery, statistics, intelligent databases, knowledge acquisition, data visualization and expert systems. The rapid growth of data and information created a need and an opportunity for extracting knowledge from databases, and both researchers and application developers have been responding to that need. KDD applications have been developed for astronomy, biology, finance, insurance, marketing, medicine, and many other fields. Core problems in KDD include representation issues, search complexity, the use of prior knowledge, and statistical inference. Topics This one-and-a-half-day workshop will bring together researchers and application developers from different areas, and focus on unifying themes such as the use of domain knowledge, managing uncertainty, interactive (human-oriented) presentation, and applications. Topics include: - Applications of KDD techniques - Interactive data exploration and discovery - Foundational issues and core problems in KDD - Machine learning/discovery in large databases - Data and knowledge visualization - Data and dimensionality reduction in large databases - Use of domain knowledge and re-use of discovered knowledge - Functional dependency and dependency networks - Discovery of statistical and probabilistic models - Integrated discovery systems/theories - Managing uncertainty in data and knowledge - Machine discovery and security and privacy issues Format We also invite working demonstrations of discovery systems. The program will include invited talks, a demo and poster session, and panel discussions. To encourage active discussion, workshop participation will be limited. Working notes will be distributed, and a selected set of papers will be considered for publication. Submissions Please submit 5 hardcopies of a short paper (a maximum of 12 single- spaced pages, 1 inch margins, and 12pt font) to reach the workshop chair on or before March 18, 1994: Usama M. Fayyad (KDD-94) AI Group M/S 525-3660 Jet Propulsion Lab, Caltech 4800 Oak Grove Drive Pasadena, CA 91109 818/306-6197 818/306-6912 (fax) Fayyad@aig.jpl.nasa.gov Organizing Committee Usama M. Fayyad, JPL; Ramasamy Uthurusamy, GM Labs (cochair); Rakesh Agrawal, IBM; Ron Brachman, AT&T Bell Labs; Leo Breiman, UC Berkeley; Nick Cercone, Simon Fraser; Peter Cheeseman, NASA AMES; Greg Cooper, U. Pittsburgh; Brian Gaines, U. Calgary; Larry Kerschberg, GMU; Willi Kloesgen, GMD; Chris Matheus, GTE; Ryszard Michalski, GMU; Gregory Piatetsky-Shapiro, GTE; Daryl Pregibon, AT&T Bell Labs; Evangelos Simoudis, Lockheed; Padhraic Smyth, JPL; Jan Zytkow, Wichita State. Models of Conflict Management in Cooperative Problem Solving A central aspect of cooperative problem solving is the avoidance, detection, and resolution of conflicts among group members. Therefore, conflict management is of great theoretical and practical interest in the development of models of multiagent problem solving. Work on conflict management has occurred in a variety of settings including multiagent planning and design, artificial intelligence and law, distributed artificial intelligence, group decision support systems, computer-supported cooperative work, software engineering, sociology, organizational science, and international relations. The goal of the workshop is to bring together academic and industrial researchers from diverse fields to exchange ideas and promote discussion about models of conflict management. Through exploring common themes, it is hoped the participants will better understand related work from other areas, and can begin to outline a general theory of conflict management across multiple domains. The workshop also aims to encourage progress toward better models of conflict management and better tools for supporting it. Topics Papers are encouraged in, but not limited to, the following topics: - What are the current theoretical underpinnings for conflict management, and how can they be applied to pra ctical problems? - How and where are theoretical and computational m odels of conflict management being used today? How do these models fare in real-world environments? - What lessons do empirical studies of conflict management have to offer for the development of the next generatio n of computational models? - How can computers support group conflict management? What are the benefits and challenges of the different approaches? - Which aspects of conflict management are generic and which are domain- specific? Can the same techniques work with human and computational participants? Format This full-day workshop will consist of four moderated sessions, each focusing on a primary subject area and including: - a moderator's overview of co mmon themes and key issues - presentations of selected papers by workshop participants: presenters will be asked to address key issues identified by the moderators - a disc uion panel, focusing on shared issues rather than on further explanation of participants' individual work. Workshop participants will also be invited to display posters describing their work. Attendance Participation is by invitation only, and will be limited to approximately 35 people. Submission Requirements Those who wish to attend the workshop should submit either: four copies of a brief research summary and statement of interest; or for those who wish to present current research at the workshop, four copies of a research abstract (no longer than 6 pages), focusing on the main contribution of the work in preference to introductory material, literature review, etc. Please include a list of keywords (e.g, design, planning, CSCW, etc.), the authors' electronic and physical address information, and indicate if you would like to display a poster at the workshop. Either hard-copy or email submissions are welcome. Submissions and questions regarding this workshop can be directed to: Mark Klein Boeing Computer Services P.O. Box 24346, 7L-64 Seattle, WA 98124-0346 USA mklein@atc.boeing.com 206/865-3412 206) 865-2964 (fax) or Susan Lander Computer Science Department University of Massachusetts Amherst, MA 01003 USA lander@cs.umass.edu 413/545-0675 413/545-1249 (fax) Organizing Committee Mark Klein (cochair), Boeing Computer Services, mklein@atc.boeing.com; Susan Lander (cochair), University of Massachusetts, lander@cs.umass.edu; D.C. Brown, Worcester Polytechnic Institute, dcb@cs.wpi.edu; V. Jagganathan, CERC, West Virginia University, juggy@cerc.wvu.edu; Simon Kaplan, University of Illinois, kaplan@marula.cs. uiuc.edu; Victor Lesser, University of Massachusetts, lesser@cs.umass.edu; Stephen Lu, University of Illinois, lu@kbesrl.me.uiuc.edu; D. Sriram, Massachusetts Institute of Technology, sriram@athena.mit.edu; Katia Sycara, Carnegie Mellon University, sycara@isl1.ri.cmu.edu. Planning for Interagent Communication Planning for inter-agent communication, whether in some natural or artificial language, requires real-time planning of resource-bounded communicative acts that change other agents' knowledge (and consequently, perhaps their actions). Communication planning is a promising domain for scale-up of planning techniques because a planner must handle larger numbers of interacting constraints than are normally attempted, apply these constraints to a larger number of choices in the development and realization of a plan, and deal with inherent uncertainties about the effects of a communicative action on a recipient. Communication planning has received some attention in (at least) the discourse planning, theories of action, robotics, and distributed AI communities. The purpose of this workshop is to bring together representatives of these communities, with the specific objectives of 1) identifying characteristic functional requirements of the communication planning problem, supported with examples; 2) identifying planning formalisms or models of atura language discourse that can provide these required functionalities, or identifying functionalities that have not been modeled, and 3) proposing future research that would facilitate progress in at least two of the relevant research communities. The workshop will be organized towards the goal of consensus on a union of these observations, i.e., a list of functional requirements paired with either identified planning formalisms or discourse models or proposals for further research. Topics Potential topics include how planning formalisms or discourse models can (when appropriate): - Generate communicative goals and select those worth pursuing, - Respect limitations of the recipient's working memory, - Rely on the recipient's inferences to achieve communicative goals, - Prevent unintentional effects not limited to the negation of explicit goals, - Deliberately overload communic ative acts to achieve multiple goals, - Address a single communicative goal in multiple ways to incr ease the likelyhood of success, - Deliberately violate normally-respected conversational rules to achieve a communicative effect, - Plan to communicate the goal-structure of the communication itself, - Plan to evaluate the success of communicative acts, - Be sensitive to prior plans and communications, and to their failures, and - Initiate concurrent execution after a temporal resource bound. Format The workshop will take place over a day and a half. The first day will be divided equally between selected presentations grouped by the issues they address and discussion of those issues. A working committee will synthesize the day's discussion in the evening, and the second morning will be devoted to presentation and discussion of a summary of conclusions and issues for further research. The workshop will be limited to 40 participants, with invitations based on submitted position papers. Submission Requirements Potential participants should submit a short (2000 words or less) position paper, preferably via email in plain text, or in postscript if figures are required. If electronic submission is not possible, submit 4 printed copies. Invited authors will have the option of including revised versions of their papers in a citable AAAI Press Technical Report to be based on the workshop. Submit to: Dan Suthers (chair) Learning Research & Development Center University of Pittsburgh 3939 O'Hara Street Pittsburgh, PA 15260 412/624-7036 412/624-9149 (fax) suthers+@pitt.edu Organizing Committee Dan Suthers, chair, University of Pittsburgh; Ed Durfee, University of Michigan, durfee@caen.engin.umich.edu; Jim Hendler, University of Maryland, hendler@cs.umd. edu; Johanna Moore, University of Pittsburgh, jmoore@cs.pitt.edu Reasoning About the Shop Floor (SIGMAN) The theme for this year's SIGMAN workshop is interaction and adaptation. The shop floor has become increasingly responsive to changes due to customer demands, management commitments, and new regulations. Together, such factors result in a complex set of interactions to which the shop floor operations must be adapted if the manufacturing process is to be competitive. Adding to the complexity is the volume of data concerning part quality, throughput, inventories, machine status, worker productivity, material handling, and finished goods. The assumptions and actions of one decision maker may easily conflict with the decisions of another and threaten havoc. The application of AI techniques to the practical operational problems of the shop floor provides a fertile testing ground for AI research, and the opportunity for improving shop floor operations. Topics Representation: Given the volume of data and the complexity of interactions, how can the dynamic environment of the shop floor be represented for both efficient inferencing and human understanding? Inference, analysis and decision-making: What mechanisms are available that allow good enough solutions to be generated in a fixed time period, but better solutions to be generated given longer periods of time? How can operations research and AI techniques, stochastic modeling and adaptive reasoning, reactive and proactive analyses, etc. be integrated for better operational decision-making that reflects current shop floor conditions? Learning: What mechanisms can learn about the shop floor state and identify cue conditions that could trigger the application of a particular operational strategy? Scheduling: How can shop-floor level schedules be integrated in a way that satisfies the many demands and constraints inherent in the meeting of higher-level goals? Fault detection, isolation, and recovery: Can the onset of shop floor contingencies be detected in such a way that the effects of the problems can be isolated and plans for recovery generated? Information management: What mechanisms can be constructed to present the human decision maker with clear and relevant information from a large volume of shop floor data? Which aspects of decision making should be computer-generated and which aspects should be left to shop floor personnel? Regulation: Given that the shop floor is constrained by the regulations of both governments and unions as to what operations can take place and how they can be executed, what mechanism can be used to propagate constraints concerning government and union regulations through the shop floor operations, scheduling and control processes? Format The one-day workshop will be organized into panel discussions related to the topics specified above. Submissions All interested in attending the workshop should submit three hard copies of a list of relevant publications, activities, etc. All interested in presenting papers should submit three hard copies of extended abstracts (no longer than five pages). Send all submissions to: Leslie Interrante (chair) Intelligent Systems Laboratory Center for Automation and Robotics University of Alabama in Huntsville Huntsville, AL 35899 205/895-6658 205/895-6733 (fax) interr@ebs330.eb.uah.edu Organizing Committee Leslie Interrante (chair); Chris Tong (co-chair), ctong@cs.rutgers.edu; David Goldstein, goldstn@ncat.edu; Hank Grant, fgrant@nsf.gov; Caroline Hayes, hayes@cs.uiuc.edu; Claude Le Pape, lepape@ilog.fr; D. Navin-Chandra, dchandra@isl1.ri.cmu.edu; Daniel Rochowiak, drochowi@cs.uah.edu; Mike Shaw, mshaw@ux1.cso.uiuc.edu, Stephen Smith. sfs@isl1.ri.cmu.edu. Spatial and Temporal Reasoning The organizers invite you to participate in examining the common aspects of the theory and application of temporal and spatial models in a spectrum of apparently disparate areas such as planning, robot control and guidance, natural language understanding, assembly plant sequencing and scheduling, temporal databases, and concurrent and distributed programming. The one- day workshop convenes researchers sharing common interests in exploring spatial or temporal problems emphasizing highly dynamic problem domains. Papers should represent current results, survey the interactions between two or more areas of spatial and temporal research, or take a position on proposed research directions that can have significant impact on one or more of the relevant fields. Contributions which span both spatial and temporal; both theory and application; both distributed systems and AI; or otherwise represent a synthesis of domains or techniques will be favored. Topics Suggested topic areas include, but are not limited to commonalties, differences, or integration of spatial and temporal reasoning; temporal knowledge representation and reasoning about concurrency; spatial or temporal ontologies, constraint satisfaction, beliefs and uncertainty, qualitative and quantitative spatial and temporal reasoning; extensions of the situation calculus; expressiveness and other evaluations of logics for time and space; propagation algorithms for spatio-temporal constraints and statistical analysis; implementations of temporal and spatio-temporal logics; temporal and active data bases and expert systems Format The opportunity for interaction and exchange among the participants will be maximized. Using a varied format of invited presentations, keynote address, panel, and open discussion, participants are expected to become involved in the discussion, potentially leading to new insights about the interfaces between space and time, AI and systems, and other related domains. The workshop will consist of approximately 40 invitees, 12 of whom will present papers. All attendees will contribute to the working notes and participate in discussions. Screening will be based on reviews and relevance to the workshop goals; a mix of views is sought. Submission Requirements Electronic submissions are solicited in TeX, Latex, or PostScript format. Papers, including references, should fit on 4 to 8 single-spaced typewritten 8.5 x 11 inch pages, in the form of an extended abstract or complete research, survey, or position paper. Submit to Frank D. Anger (fdang@dcs106.dcsnod.uwf.edu) or Rasiah Loganantharaj (logan@cacs.usl.edu) Frank D. Anger CS Dept., Univ of West Florida Pensacola, FL 32514 USA 904/474-3022 904/474-3129 (fax) Organizing Committee Tony Cohn, Univ of Leeds, agc@scs.leeds. ac.uk; Hans W. Guesgen, Univ of Auckland, hans@cs.auckland.ac.nz; Gerard Ligozat, LIMSI/CNRS & Univ Paris-Sud, ligozat@limsi.fr; Nikki Pissinou, Univ of SW Louisiana, pissinou@cacs.usl.edu; Rita V. Rodriguez, Univ of W Florida, rrodrigu@dcs106.dcsnod. uwf.edu; Andre Trudel, Acadia Univ, trudel@acadiau.ca Validation and Verification of Knowledge-Based Systems Ever since knowledge-based systems (KBS's) were first introduced, establishing their quality has been a difficult, persistent problem. However, in the last few years new techniques have appeared which address this problem. Workshops on this topic have been held at each of the last six AAAI national conferences. The specific objectives of this year's workshop is to focus upon three areas: The theory and application of formal techniques of verification and validation (V&V) to KBS's; the validation and verification of very large KBS's including embedded systems; and consideration of techniques applicable to representations other than rule-based production systems. Topics Formal Techniques: The application of formal methods and tools to KBS's specification and development; life-cycle issues in the development of knowledge-based systems including metrics; and formal denotational semantic specification issues in relation to knowledge representation. Very Large KBS: State of the art papers from industry on the V&V of large KBS's; technical issues in the V&V of very large systems. Representational Issues: V&V of embedded or hybrid KBS's, including the relationships between the KBS and V&V areas such as neural networks, case-based reasoning, parallel implementations, very large scale systems, and frame-based, semantic networks and hybrid representations. Format This one-day workshop will be divided into five sessions, two in each of the morning and the afternoon, and an informal working lunch session. Each session may include sequences of short paper presentations, longer single paper presentations, and discussion sessions. Short paper presentations will be selected and grouped according to the theses of the workshop. Each longer paper presentation will focus on a particular topic. Attendance The workshop is limited to 50 participants to encourage in-depth discussion of topics. Participants will be chosen by the program committee on the basis of submitted materials, or extensive KBS V&V experience and a willingness to serve as discussant. Submission Requirements Participants should submit two copies of either an unpublished technical paper (not to exceed 10 double-spaced pages) or unpublished extended (1-2 page) abstract on the V&V of KBS. Participants with KBS V&V experience who wish to attend and who are willing to serve as discussants should provide details of their qualifications for this role. Submit to: Robert T. Plant (Chair) Department of Computer Information Systems, University of Miami Coral Gables, Florida 33124 305/ 284-6105 305/284 5161(fax) rplant@umiami.miami.edu Organizing Committee Trevor Bench-Capon, U. Liverpool, T.J.M. Bench-Capon@csc.liv.ac.uk; Rose Gamble, U. Tulsa, gamble@tara.mcs. utulsa.edu; Christopher Landauer, Aero-space Corp., cal@aero.org; Lance Miller