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Reasoning About Knowledge



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Reasoning About Knowledge (COM S 676):
Course Description

Reasoning about knowledge -- particularly the knowledge of agents who reason about the world and each other's knowledge -- was once the exclusive province of philosophers and puzzle solvers. More recently, this type of reasoning has been shown to play a key role in a surprising number of contexts, from understanding conversations to the analysis of distributed computer algorithms.

This course provides a general discussion of approaches to reasoning about knowledge and its applications to distributed systems, artificial intelligence, and game theory. We'll start by examining the well-known ``muddy children puzzle'', which demonstrates the subtleties of reasoning about knowledge of a group. We then consider a simple yet powerful formal semantic model for knowledge and a language for reasoning about knowledge whose underlying idea is that of ``possible worlds''. The rest of the course develops the model and show how it can be used to ascribe knowledge to agents in multi-agent systems. This allows us to better understand notions such as coordination and agreement. The definitions lead naturally to a notion of knowledge-based programs, a high-level tool for designing and analyzing systems.

The course follows closely the material in the book Reasoning About Knowledge, which actually was inspired by early versions of the course.