CSCI 561a Fall 2001 Timetable

Lecture	Date	Reading	Notes
01 Introduction	08/28/01	AIMA Ch 1
02 Intelligent Agents	08/30/01	AIMA Ch 2
03 LISP 1	09/04/01	ACL Ch 2, 3, 5
04 LISP 2	09/06/01	ACL Ch 2, 3, 5
05 LISP 3	09/11/01	ACL Ch 6, 11, 17
06 LISP 4	09/13/01	ACL Ch 6, 11, 17
07 Problem solving and search 1	09/18/01	AIMA Ch 3
08 Problem solving and search 2	09/20/01	AIMA Ch 3
09 Uninformed search	09/25/01	AIMA Ch 3
10 Informed search 1	09/27/01	AIMA Ch 4
11 Informed search 2	10/02/01	AIMA Ch 4
12 Game playing 1	10/04/01	AIMA Ch 5
MIDTERM EXAM	10/09/01	All of the above
13 Game playing 2	10/11/01	AIMA Ch 5
14 Agents that reason logically 1	10/16/01	AIMA Ch 6
15 Agents that reason logically 2	10/18/01	AIMA Ch 6
16 First-order logic 1	10/23/01	AIMA Ch 7
17 First-order logic 2	10/25/01	AIMA Ch 7
18 Building a knowledge base	10/30/01	AIMA Ch 8
19 Inference in first-order logic 1	11/01/01	AIMA Ch 9
20 Inference in first-order logic 2	11/06/01	AIMA Ch 9
21 Inference in first-order logic 3	11/08/01	AIMA Ch 9
22 Logical reasoning systems	11/13/01	AIMA Ch 10
23 Planning 1	11/15/01	AIMA Ch 11
24 Planning 2	11/20/01	AIMA Ch 11
Thanksgiving Recess	11/22/01
25 Expert systems 1	11/27/01	[handout]
26 Expert systems 2	11/29/01	[handout]
27 Towards intelligent machines	12/04/01	AIMA Ch 25
28 Overview and summary	12/06/01	AIMA Ch 27
FINAL EXAM -- 2:00-4:00pm	12/13/01	All of the above

CSCI 561a Fall 2001 Syllabus

01-Introduction. [AIMA Ch 1] Course Schedule. Homeworks, exams and grading. Course material, TAs and office hours. Why study AI? What is AI? The Turing test. Rationality. Branches of AI. Research disciplines connected to and at the foundation of AI. Brief history of AI. Challenges for the future. Overview of class syllabus.

02-Intelligent Agents. [AIMA Ch 2] What is an intelligent agent? Examples. Doing the right thing (rational action). Performance measure. Autonomy. Environment and agent design. Structure of agents. Agent types. Reflex agents. Reactive agents. Reflex agents with state. Goal-based agents. Utility-based agents. Mobile agents. Information agents.

03-LISP 1. [ACL Ch 2, 3, 5] How can we develop AI software? Why study LISP? Syntax. Prefix notation. Predicates. Functions. Recursion. Variables. Input/Output.

04-LISP 2. [ACL Ch 2, 3, 5] Lists. Sets. Sequences, trees, stacks. Blocks. Conditionals. Data structures.

05-LISP 3. [ACL Ch 6, 11, 17] Function parameters. Manipulating functions. Lambda expressions. Function object symbols.

06-LISP 4. [ACL Ch 6, 11, 17] Multiple return values. Special functions. Utility functions. Example: function builders. Object-oriented programming. Methods on data structures.

07-Problem solving and search 1. [AIMA Ch 3] Example: measuring problem. Types of problems. More example problems. Basic idea behind search algorithms.

08-Problem solving and search 2. [AIMA Ch 3] Complexity. Combinatorial explosion and NP completeness. Polynomial hierarchy.

09-Uninformed search. [AIMA Ch 3] Depth-first. Breadth-first. Uniform-cost. Depth-limited. Iterative deepening. Examples. Properties.

10-Informed search 1. [AIMA Ch 4] Best-first. A* search. Heuristics. Hill climbing. Problem of local extrema. Simulated annealing.

11-Informed search 2. [AIMA Ch 4] Best-first. A* search. Heuristics. Hill climbing. Problem of local extrema. Simulated annealing.

12-Game playing 1. [AIMA Ch 5] The minimax algorithm. Resource limitations. Aplha-beta pruning.

14-Agents that reason logically 1. [AIMA Ch 6] Knowledge-based agents. Logic and representation. Propositional (boolean) logic.

15-Agents that reason logically 2. [AIMA Ch 6] Inference in propositional logic. Syntax. Semantics. Examples.

16-First-order logic 1. [AIMA Ch 7] Syntax. Semantics. Atomic sentences. Complex sentences. Quantifiers. Examples. FOL knowledge base. Situation calculus.

17-First-order logic 2. [AIMA Ch 7] Describing actions. Planning. Action sequences.

18-Building a knowledge base. [AIMA Ch 8] Knowledge bases. Vocabulary and rules. Ontologies. Organizing knowledge.

19-Inference in first-order logic 1. [AIMA Ch 9] Proofs. Unification. Generalized modus ponens. Forward and backward chaining.

20-Inference in first-order logic 2. [AIMA Ch 9] Proofs. Unification. Generalized modus ponens. Forward and backward chaining.

21-Inference in first-order logic 3. [AIMA Ch 9] Proofs. Unification. Generalized modus ponens. Forward and backward chaining.

22-Logical reasoning systems. [AIMA Ch 10] Indexing, retrieval and unification. The Prolog language. Theorem provers. Frame systems and semantic networks.

23-Planning 1. [AIMA Ch 11] Definition and goals. Basic representations for planning. Situation space and plan space. Examples.

24-Planning 2. [AIMA Ch 11] Definition and goals. Basic representations for planning. Situation space and plan space. Examples.

25-Expert systems 1. [handout] What are expert systems? Applications. Pitfalls and difficulties. Rule-based systems. Comparison to traditional programs. Building expert systems. Production rules. Antecedent matching. Execution. Control mechanisms.

26-Expert systems 2. [handout] Overview of modern rule-based expert systems. Introduction to CLIPS (C Language Integrated Production System). Rules. Wildcards. Pattern matching. Pattern network. Join network.

27-Towards intelligent machines. [AIMA Ch 25] The challenge of robots: with what we have learned, what hard problems remain to be solved? Different types of robots. Tasks that robots are for. Parts of robots. Architectures. Configuration spaces. Navigation and motion planning. Towards highly-capable robots.

28-Overview and summary. [all of the above] What have we learned. Where do we go from here?