| 2000- | Adaptive Control of NASA Life Support Systems
Developing learning-based controllers for life-support systems. These systems regulate the levels of air, water, food and energy for long-duration crew support in space. The associated control problems are dynamic, nonstationary, and safety-sensitive, requiring novel active-learning techniques. Work with Jeff Schneider, Leslie Kaelbling, and David Kortenkamp, in progress. |
| 2000 | Internet Auction Trading Strategies
Participated in the ICMAS-2000 Trading Agent Competition (TAC). This contest involved programming a travel agent to buy and sell airline tickets, hotel rooms, and entertainment tickets in 28 simultaneous Internet auctions, so as to construct profitable travel packages at minimum cost. Our entry included innovations in real-time resource allocation, pricing of single resources given combinatorial utilities, and risk mitigation. Work with Amy Greenwald.
Results: winner (out of 25) in preliminary round; co-winner (out of 12) in finals. |
| 1999- | Optimal Route Planning Under Time-Dependent Uncertainty
Developed new representations and solutions for time-sensitive stochastic planning problems. Applications to telescope experiment scheduling and multimodal transportation planning. Work with Michael Littman and Mike Mitzenmacher, in progress. [2] [1] [19] |
| 1996- | Learning Evaluation Functions for Global Optimization
Combined dynamic programming, function approximation and local search techniques into an algorithm that automatically constructs high-quality evaluation functions for fast combinatorial optimization. Applications to VLSI design, medical robotics, satisfiability, Bayes net structure-finding, geographic visualization, and information retrieval. Ph.D. thesis work. [18] [3] [20] [6] [8] [10] [13] [21] |
| 1994- | Scaling Up Reinforcement Learning / Value Function Approximation
Developed new algorithms for Value Function Approximation, solving large-scale high-dimensional control and scheduling problems with approximate dynamic programming. Work with Andrew Moore. [5] [7] [14] [15] [21] [22] |
| 1996 | Information Retrieval / Web Indexing / Machine Learning
Developed LASER, a machine-learning-based search engine for the World Wide Web. Using non-intrusive feedback gathered from system users doing Web searches, it optimizes its retrieval function so as to provide better page rankings. Work with Dayne Freitag and Thorsten Joachims. [12] |
| 1995-96 | Anonymizing Proxy System for the World Wide Web
Developed the Anonymizer, a custom proxy server that enables Web users to visit sites without revealing personal information such as their email address and Internet hostname. In April 1997, the system was sold to Infonex, Inc. and made available to the public at www.anonymizer.com. [9] Sample of media coverage:
|
| 1995-96 | Internet Privacy Demonstration
 Created a script to demonstrate how Internet users may reveal personal information to every web site they visit. This script won a Netscape "Bugs Bounty" award in January 1996 and was featured for several years on the home page of the Center for Democracy and Technology. [9]
|
| 1993-94 | Reinforcement Learning for Network Routing / Multi-Agent Learning
Invented Q-routing, a parallel distributed reinforcement-learning algorithm for routing packet traffic in a computer network. The routing tables adapt to varying network topologies and traffic loads. This study has been followed up by at least five separate groups of researchers. Work with Michael Littman. [16] [17] |
| 1992-93 | Artificial Neural Network algorithms
Designed and tested extensions to cascading and modular neural network architectures. Work with Frank Fallside, Tony Robinson and Scott Fahlman. [27] |
| 1992-94 | Self-Learning Backgammon Software
Wrote software combining temporal-difference learning and modular neural networks in order to train, from scratch, an expert-level computer backgammon player.  [27]
|
| 1993- | Web site design |
| 1986-95 | Sole proprietor, BOYAN Communications
Authored BOYAN Communications, a best-selling PC modem program. Maintained, documented, and marketed (via Shareware and mail-order distribution) four major versions of the software over a ten-year life cycle. |
| 2000-2003 | Editorial Board, Machine Learning Journal |
| 2000 | Co-organizer, AAAI-2000 Workshop on Artificial Intelligence for Web Search |
| 2000 | Organizer, MIT Statistical AI Reading Group |
| 1999 | Organizer, Workshop on Statistical Machine Learning for Large-Scale Optimization, Stockholm, Sweden
I co-organized this IJCAI workshop with Wray Buntine. An edited version of the proceedings will appear in Neural Computing Surveys. [18]
|
| 1999 | Judge, Siemens Westinghouse Science and Technology Competition, Princeton, NJ |
| 1998 | Judge, Santa Clara Valley Science and Engineering Fair, San Jose, CA |
| 1998 | Invited speaker, Symposium on Applications of Reinforcement Learning, Stanford University
I was one of fifteen invited speakers at this symposium.
|
| 1997 | Invited speaker, NSF/CNPq Joint Workshop on Intelligent Robotic Agents, Porto Alegre, Brazil |
| 1996 | Invited speaker, NSF Reinforcement Learning workshop, Harper's Ferry, WV
I was one of three graduate students invited to participate in this national workshop.
|
| 1995 | Organizer, Workshop on Value Function Approximation, Tahoe City, CA
I co-organized this Machine Learning Conference workshop with Andrew Moore and Rich Sutton. |
| 1995 | Teaching Assistant, How to Think (Like a Computer Scientist)
Instructor: Rudich.
This is an undergraduate discrete mathematics course, but with an unusual emphasis on developing the thought processes involved in problem-solving, instead of just presenting techniques and answers. |
| 1993 | Teaching Assistant, Artificial Neural Networks (graduate course)
Instructors: Touretzky, Waibel, Fahlman, and Pomerleau.
Duties included: lecturing, preparing homework assignments (competitive learning, backpropagation, reinforcement learning), supervising class projects, and grading. |
| 1992-1997 | Organizer, CMU Reinforcement Learning Group
I coordinated weekly talks, inviting speakers from both inside and outside CMU. (Log of past talks)
|
| 1993- | Paper Referee: |
| 1986-93 | Mathematics teacher, Johns Hopkins University Center for Talented Youth residential summer program 
I attended the CTY program for three years as a teenager, and returned to it on the instructional staff for many summers afterward. As an instructor, I guided classes of 15-20 bright students through an intensive, individually-paced mathematics course: in three weeks, a typical CTY student masters an amount of material which would otherwise be covered over 1-2 years of high school. I also presented a wide range of fun extra topics, such as number theory, the Cantor set and infinity, and recursive functions. In 1991, I initiated the use of Mathematica in the precalculus classroom. |
| [1] | ![[13 pages, gzipped postscript, 125K]](ps.gif) ![[13 pages, Adobe PDF, 246K]](pdf.gif) Boyan, J. A. and M. Mitzenmacher. "Improved Results for Route Planning in Stochastic Transportation Networks." Accepted to the 12th Annual Symposium on Discrete Algorithms (SODA), 2001. |
| [2] | Boyan, J. A. and M. L. Littman. "Exact Solutions to Time-Dependent MDPs." To appear in Advances in Neural Information Processing Systems (NIPS). MIT Press, 2001.
(Selected for oral presentation.) |
| [3] | Boyan, J. A. and A. W. Moore. "Learning Evaluation Functions to Improve Local Search." Journal of Machine Learning Research, to appear, 2000. |
| [4] | Boyan, J. A. "Technical Update: Least-Squares Temporal Difference Learning." Machine Learning Journal, to appear, 2000. |
| [5] | Boyan, J. A. "Least-Squares Temporal Difference Learning." In Bratko, I., and Dzeroski, S., eds., Machine Learning: Proceedings of the Sixteenth International Conference (ICML), 1999.
(Selected as ICML-99 Best Paper. One of 152 submissions received this honor.) |
| [6] | Boyan, J. A. and A. W. Moore. "Learning Evaluation Functions for Global Optimization and Boolean Satisfiability." Fifteenth National Conference on Artificial Intelligence (AAAI), 1998.
(Selected as an AAAI-98 Outstanding Paper. Three of 475 submissions received this honor.) |
| [7] | Schneider, J. G., J. A. Boyan and A. W. Moore. "Value Function Based Production Scheduling." Machine Learning: Proceedings of the Fifteenth International Conference (ICML), 1998. Also presented at Symposium on Applications of Reinforcement Learning, Stanford, March 1998. |
| [8] | Moore, A. W., J. G. Schneider, J. A. Boyan and M. S. Lee. "Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions." Machine Learning: Proceedings of the Fifteenth International Conference (ICML), 1998. |
| [9] | Boyan, J. A. "The Anonymizer: Protecting User Privacy on the Web." Computer-Mediated Communication Magazine, 4 (9), September 1997. |
| [10] | Boyan, J. A. and A. W. Moore. "Using Prediction to Improve Combinatorial Optimization Search." Sixth International Workshop on Artificial Intelligence and Statistics (AISTATS), 1997. |
| [11] | Boyan, J. A. "Value Function Approximation Applied to Combinatorial Optimization." Second International Conference on Computational Intelligence and Neuroscience (ICCIN), Research Triangle Park, NC, 1997. |
| [12] | Boyan, J. A., D. Freitag and T. Joachims. "A Machine Learning Architecture for Optimizing Web Search Engines." Proceedings of the AAAI workshop on Internet-Based Information Systems, AAAI Technical Report WS-96-06, 1996. |
| [13] | Boyan, J. A. "A Reinforcement Learning Framework for Combinatorial Optimization." (student abstract) Thirteenth National Conference on Artificial Intelligence (AAAI), 1996. |
| [14] | Boyan, J. A. and A. W. Moore. "Learning Evaluation Functions for Large Acyclic Domains." In L. Saitta (ed.), Machine Learning: Proceedings of the Thirteenth International Conference (ICML). Morgan Kaufmann, 1996. |
| [15] | Boyan, J. A., and A. W. Moore, "Generalization in Reinforcement Learning: Safely Approximating the Value Function." In Tesauro, G., D. S. Touretzky, and T. K. Leen (eds.), Advances in Neural Information Processing Systems 7 (NIPS). MIT Press, 1995.
(Selected for oral presentation. Approximately 30 out of 500 submissions received this honor.) |
| [16] | Boyan, J. A., and M. L. Littman, "Packet routing in dynamically changing networks: A reinforcement learning approach." In Cowan, J. D., Tesauro, G., and Alspector, J. (eds.), Advances in Neural Information Processing Systems 6 (NIPS). Morgan Kaufmann, 1994. |
| [17] | Littman, M. L. and J. A. Boyan. "A Distributed Reinforcement Learning Scheme for Network Routing." In Alspector, J., Goodman, R., and Brown, T. X. (eds.), Proceedings of the International Workshop on Applications of Neural Networks to Telecommunications, October 1993. Also appeared as: Carnegie Mellon Technical Report CMU-CS-93-165. |
| [18] | Boyan, J. A. and W. L. Buntine, eds. "Statistical Machine Learning for Large-Scale Optimization." Neural Computing Surveys 3, 2000. |
| [19] | Boyan, J. A. and M. L. Littman. "Representations and Algorithms for Time-Dependent MDPs." Presented at the workshop on "Beyond MDPs", UAI-2000. |
| [20] | Boyan, J. A. "Learning Evaluation Functions for Global Optimization." Ph.D. thesis, Carnegie Mellon University, August 1998. (U.S. Copyright # TX4 309 277.) Also appeared as: Carnegie Mellon Technical Report CMU-CS-98-152. (web page)
Oral defense given at CMU, May 1998. Also presented at Stanford University, UC Berkeley, AT&T Labs, SRI International, NASA Ames Research Center, Compaq CRL, MERL, Microsoft Research, i2 Research, and NEC Research.
|
| [21] | Boyan, J. A. "Learning Evaluation Functions." Ph.D. Thesis Proposal, CMU, June 1996. (web page)
|
| [22] | Boyan, J. A., A. W. Moore, and R. S. Sutton, Editors. "Proceedings of the Workshop on Value Function Approximation, Machine Learning Conference 1995." Carnegie Mellon Technical Report CMU-CS-95-206. workshop home page |
| [23] | Boyan, J. A. "Active Learning for Optimal Control in Acyclic Domains." In Proceedings of AAAI Symposium on Active Learning, Autumn 1995. |
| [24] | Boyan, J. A. "Two Algorithms for Robust VFA By Working Backwards." Presented at ML95 workshop on Value Function Approximation, July 1995. |
| [25] | Boyan, J. A. "Safely Approximating the Value Function." Presented at Action Learning workshop, MIT, March 1995. Similar talks given at Brown University and the University of Massachusetts, 1995, and Stanford University, 1994.
|
| [26] | Boyan, J. A. "MAESTRO 1.0: A Modular Neural Network for Learning Context-Dependent Backgammon Strategies by Self-Play." Presented at the Fourth International Conference on Computer Games, London, August 1992. |
| [27] | Boyan, J. A. "Modular Neural Networks for Learning Context-Dependent Game Strategies." Master's thesis, Department of Engineering and Computer Laboratory, University of Cambridge, 1992. |
![[photo, 10/99]](./oct99.jpg)
NASA Ames Research Center
Carnegie Mellon University
University of Cambridge
University of Chicago
