|
|
[ Administrivia | Topics & Schedule | Problem Sets | Project | Resources ]
The primary goal of this class is to provide a rigourous introduction to Artificial Intelligence, explaining the challenges inherent in building an intelligent system and describing the main techniques and tools. We will focus on search, knowledge representation, constraint satisfaction, planning with some material on learning and reasoning about uncertainty. A secondary goal of the course is to teach how to read and analyze research papers. Thus some of the reading will be in the textbook (or a survey paper) and some will be recent conference papers; in the latter case, students will write program-committee style reviews. There will be several short problem sets and a modest project.
Class schedule: M, W
Office hours: Monday
TA:
The (required) textbook is Russell & Norvig AI a Modern Approach, (Prentice Hall) 2nd edition, 2003. (Note: this book is much improved over the previous edition). We will also assign readings off the WWW.
Your final grade will be assigned based on the following (tentative weighting):
Instructions for reviewing papers
Date |
Topic |
Reading due |
Lecture Slides |
Sept 29 |
Introduction, administrivia, agents |
None |
|
Oct 1 |
Agents; problem spaces; search (part 1) |
R&N Ch 2, 3 |
|
Oct 6 |
Informed search; IDA*, local search; GA |
R&N Ch 4 |
|
Oct 8 |
Heuristics & adversary search |
R&N Ch 6 |
|
Oct 13 |
Propositional logic |
R&N Ch 7 |
|
Oct 15 |
Class canceled |
R&N Ch 8; Ch 9 thru p 278; Section 10.3 |
|
Oct 20 |
Knowledge Representation (KR) |
||
Oct 22 |
KR |
|
|
Oct 27 |
Learning |
R&N ch 18 |
|
Oct 29 |
… continued |
None |
|
Nov 3 |
Planning |
R&N Section 10.3; ch 11; R&N ch5 |
|
Nov 5 |
Satplan 7 graphplan |
||
Nov 10 |
Graphplan (cont), heuristics & time |
|
|
Nov 12 |
MDPs, Value & Policy Iteration |
R&N ch 17 |
|
Nov 17 |
Uncertainty planning using ADDs |
||
Nov 19 |
Abstraction & reachability in MDPs |
||
Nov 24 |
Partial observability (POMDPs) |
R&N 17.4, 17.5 & POMDP Review |
|
Nov 26 |
No class |
None |
None |
Dec 1 |
Reinforcement Learning |
R&N Ch 21 |
|
Dec 3 |
Tournament 1 & Applic to Ubicomp |
None |
|
Dec 8 |
Intelligent Internet Systems |
||
Dec 10 |
Tournament 2 & Review |
None |
None |