The course is a basic introduction to artificial intelligence covering problem solving, heuristic search, knowledge representation, deduction,

planning, uncertain knowledge and reasoning, and learning. The course will focus on understanding concepts and algorithms rather than programming,

although there will be homeworks involving programming they must be written in Java (version 1.2.1) to run on the instructional Sun Sparcstations.

(A page of useful Java-related links and tips is available.).

Chapter numbers refer to the text: Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig

1. Introduction
   Chapters 1-2. Definition and history of AI
2. Problem Solving
   Chapters 3-5. Uninformed search, informed (heuristic) search, game playing.
3. Knowledge and Reasoning
   Chapters 6-7, 9-10 Representing knowledge, first-order logic, deduction and resolution, inheritance, and non-monotonic inference.
4. Planning
   Chapter 11. Representing actions, situation calculus, total-order and partial-order planning algorithms.
5. Uncertain Reasoning
   Chapters 14-15. Probability theory, Bayesian inference, Bayesian networks: representation and inference.
6. Learning
   Chapters 18,19 and 21. Inductive learning for classification, decision-tree induction, neural-networks and relational learning: representation and training.

The work in the course will consist of 5-6 homework assignments (about one every two weeks), a midterm exam, and a final exam. Your solutions will be partially automatically graded, so they must be written to run on the instructional Sun Sparcstations. Homework assignments will usually involve programming tasks that are to be done in Java (version 1.1). (A page of useful Java-related links and tips is available.)