CSCI 561 Spring 2006 Timetable

Lecture	Date	Reading	Notes
01 Introduction	01/10/06	AIMA Ch 1
02 Intelligent Agents	01/12/06	AIMA Ch 2
03 Problem solving and search 1	01/17/06	AIMA Ch 3	HW1 out
04 Problem solving and search 2	01/19/06	AIMA Ch 3
05 Uninformed search	01/24/06	AIMA Ch 3
06 Informed search 1	01/26/06	AIMA Ch 4
07 Informed search 2	01/31/06	AIMA Ch 4	HW1 due
08 Game playing 1	02/02/06	AIMA Ch 5	HW2 out
09 Game playing 2	02/07/06	AIMA Ch 5
10 Agents that reason logically 1	02/09/06	AIMA Ch 6
11 Agents that reason logically 2	02/14/06	AIMA Ch 6
12 First-order logic 1	02/16/06	AIMA Ch 7	HW2 due
13 First-order logic 2	02/21/06	AIMA Ch 7
MIDTERM EXAM - 5:00-6:20pm	02/23/06	All of the above	HW3 out
14 Building a knowledge base 1	02/28/06	AIMA Ch 8
15 Building a knowledge base 2	03/02/06	AIMA Ch 8
16 Inference in first-order logic 1	03/07/06	AIMA Ch 9
17 Inference in first-order logic 2	03/09/06	AIMA Ch 9	HW3 due
Spring break - NO CLASS	03/14/06
Spring break - NO CLASS	03/16/06
18 Inference in first-order logic 3	03/21/06	AIMA Ch 9	HW4 out
19 Logical reasoning systems	03/23/06	AIMA Ch 10
20 Planning	03/28/06	AIMA Ch 11
21 Introduction to CLIPS	03/30/06	Handout
22 Fuzzy Logic 1	04/04/06	[handout]
23 Fuzzy Logic 2	04/06/06	[handout]	HW4 due
24 Neural Networks 1	04/11/06	[handout]	HW5 out
25 Neural Networks 2	04/13/06	[handout]
26 Genetic Algorithms	04/18/06	[handout]
27 Towards intelligent machines	04/20/06	AIMA Ch 25
28 Overview and summary	04/25/06	AIMA Ch 27	HW5 due
29 Review Session	04/27/06
FINAL EXAM - 4:30-6:30pm	05/09/06	All of the above

CSCI 561 Spring 2005 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-Problem solving and search 1. [AIMA Ch 3] Example: measuring problem. Types of problems. More example problems. Basic idea behind search algorithms.

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

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

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

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

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

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

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

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

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

14/15-Building a knowledge base. [AIMA Ch 8] Knowledge bases. Vocabulary and rules. Ontologies. Organizing knowledge.

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

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

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

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

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

21-Introduction to CLIPS. [handout] Syntax, user interface, definign a rule-base, inference. Examples.

22/23-Fuzzy logic. [Handout] Introduction to fuzzy logic. Linguistic hedges. Fuzzy inference. Examples.

24/25-Neural Networks. [handout] Perceptrons, Hopfield networks, self-organizing feature maps. How to size a network? What can neural network achieve?

26-Genetic Algorithms. [handout] Overview of genetic algorithms and their use in optimization problame.

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?