AI Lunch and Seminar

Scott E. Fahlman - Knowledge-Based AI Using Scone

In the early days of the AI field, the focus was mostly on symbolic knowledge, reasoning, and search, plus a little bit of machine learning to gather the necessary knowledge. More recently, the focus has shifted almost completely to ML, Big Data, and Deep Learning, and there has been some exciting progress in these areas. I will argue that for human-like, human-level AI, we are going to need both approaches: the ML stuff to handle the sensory-motor tasks, and the symbolic stuff for semantics, complex reasoning, and "conscious" thought.

In the remainder of the talk, I will give a high-level overview of the open-source Scone knowledge-base system, which my research group has been working on for most of the last decade. I will describe how Scone handles inheritance of information through the "is a" hierarchy, default reasoning with exceptions, and statements about statements, and how we scale the system up to millions of entities and statements -- on a laptop.

Perhaps the most unusual feature of Scone is its multiple-context mechanism, which allows us to represent many slightly different world-models within the same knowledge base. Scone's contexts are used for modeling and reasoning about information that changes from one time-point to another; hypotheses and counter-factuals; the different knowledge-states and belief-states of various characters; lies and deception; and in many other ways. Contexts are our secret weapon and our Swiss Army Knife.

Finally, I will give a quick overview of the Scone project's current status and what we are working on, now and in the future.