## Your grade will be based on your project results and class presentations (50%) and your final exam (50%). Homework is mandataory but will not contribute to your final grade (unless you fail to submit your HW). It's very important that you try each HW exercise, it's not important that you get it right the first time.

Homework Solutions:

[HW-1 Solutions]

[HW-2 Solutions]

[HW-3 Solutions]

[HW-4 Solutions-partA; HW4-solutions-partB]

## Week 3: Reading-book: Chapter 3 Reading-paper: Introduction Ant Colony Optimization Exercises: 3.5 (book) + HW-Ch3 [doc] [pdf] (due Monday Oct 12 midnight in EEE dropbox)

Week 4:
Reading-paper: Game of Life as a Turing Machines
Exercises: HW -Ch4 [doc][pdf] (due Monday Oct 19 midnight in EEE dropbox)

Week 5:
Exercises: HW Ch5 [doc][pdf] (due Monday Oct. 26 midnight in EEE dropbox)

Week 6:
Exercises: HW Ch. 6 [doc] [pdf]

Week 7:
Exercises: HW Ch. 7 [doc] [pdf]

Week 8:
Exercises: HW Ch.8 page 268-270: 8.3; 8.6; 8.7; 8.8; 8.15. (due Monday Nov. 16 midnight in EEE dropbox)

Week 9:
Reading-paper: Paper on Godel's Theorem amd the Mind
Exercises: HW Ch. 9 page 315-318: 9.3; 9.4; 9.9; 9.10a; 9.18; 9.19

## Syllabus: (incomplete)

The following represents a very preliminary syllabus. Expect significant changes.

Introduction: Goals, history (Ch.1)
Agents (Ch.2)
Uninformed Search (Ch.3)
Informed Search (Ch.4 NOT  sec.4.5 and after)
Constraint satisfaction (Ch.5).
Games (Ch.6)
Propositional Logic (Ch.7 NOT "circuit based agents" on page 227 and after)
First Order Logic (Ch.8 NOT sec. 8.4 and after)
Inference in first order logic (Ch.9 NOT including "Completeness of Resolution" and after, p.300)
Uncertainty (Ch.13)
Planning
Reinforcement Learning
AI: Present and Future (Ch 27)

Final: Wed. Dec 9, 4-6 pm