Objectives:
Applications of logic. Topics include first order predicate calculus as a reasoning agent, deductive reasoning and resolution refutation, nonmonotonic reasoning, induction, reasoning with uncertain information, reasoning about knowledge and belief, meta level representation and reasoning and and architectures for intelligent agents.
Prerequisites: CS480/580 or consent of the instructor
Textbook:
Michael R. Genesereth and Nils J. Nilsson Logical Foundations of Artificial Intelligence Morgan Kaufmann Publishers, Inc. 1987
References:
Various references cited in the textbook Various journals and conference proceedings in CS and AI
Outline:
1. Overview 2. Declarative knowledge representation. Applications: blocks world, circuits, algebra, natural language. 3. Logical inference 4. Resolution principle: concept, method, strategies. Applications: finding answers from databases, diagnosing circuit faults, proving mathematical theorems. 5. Nonmonotonic reasoning Applications: decision making with best, insufficient knowledge. 6. Generalization and induction Applications: learning, perception. 7. Knowledge vs. belief, and reasoning with uncertainty Applications: expert systems. 8. Metaknowledge and metareasoning Applications: building more efficient expert systems. 9. States, actions, and changes Applications: robot actions.