Schedule and Handouts

(Subject to revision)
To download a postscript version of the lecture slides for a particular day, click on the corresponding topic. All reading assignments refer to Russell and Norvig unless otherwise noted.

Date Lecturer Topic Reading Due Out
Tu. Aug 29Carbonell Introduction to AI, Basic Search Methods (DFS, BFS, BiBFS, ...)
note: only a subset of the lecture slides are available online; see the course administrator for a complete copy
additional handout: syllabus
Ch. 3   
Th. Aug 31Carbonell Heuristic Functions in Search (HC, Best-first, Beam, B-and-B, A*) Ch. 4  HW1
Tu. Sep 5Carbonell Beyond Basic Search Methods     
Th. Sep 7Veloso Bi-polar Search (Minimax, Alpha-beta), Game playing
Ch. 5   
Tu. Sep 12Veloso Knowledge Representation, First-order Logic Ch. 6   
Th. Sep 14Veloso Resolution, Unification, Model-based Reasoning Ch. 9 - resolution for
propositional logic only, normal form
Tu. Sep 19Carbonell Multi-valued Logics, Non-monotonic Reasoning, Semantic Nets, Frames     
Th. Sep 21Carbonell Intro to Natural Language Processing (Parsing, ATNs, Case Frames)
note: only hardcopies of the lecture slides are available; see the course administrator
Sec. 22.4, 22.6, 22.7
AI encyclopedia article
Tu. Sep 26Veloso Constraint Satisfaction, Constraint-based Scheduling Sec. 4.4   
Th. Sep 28Veloso Planning I: State-Space Planning   HW2HW3
Tu. Oct 3Veloso Planning II: Plan-Space Planning, Comparison Ch. 11   
Th. Oct 5Veloso Planning III: Graphplan, Satplan, Comparison (Lecture slides included in Planning II above)     
Tu. Oct 10Veloso/Carbonell Midterm Review   HW3 
Th. Oct 12  MIDTERM Midterm exam solutions     
Tu. Oct 17Veloso Conditional Planning Ch. 13  HW4
Th. Oct 19Veloso Earthware Symposium, McConomy Auditorium     
Tu. Oct 24Prof. Yiming Yang
(guest lecturer)
Decision Trees and Text Categorization Ch. 18   
Th. Oct 26Carbonell Intro to Information Retrieval: Vector Space Methods, Search Engines     
Tu. Oct 31Carbonell Rule-based Systems and Knowledge Acquisition     
Th. Nov 2Carbonell Supervised and Unsupervised Machine Learning Methods     
Tu. Nov 7Veloso Neural Networks Ch. 19 HW4HW5
Th. Nov 9Veloso MDPs and Deterministic Reinforcement Learning Ch.13 - Mitchell's "Machine Learning" book   
Tu. Nov 14Veloso Nondeterministic Reinforcement Learning (Lecture slides included in previous class)     
Th. Nov 16Veloso Exercises in Reinforcement Learning     
Tu. Nov 21Veloso Probability Theory and Bayes Networks Textbook: 14.2,14.3,15.1,15.2 HW5HW6
Tu. Nov 28Carbonell Real-time AI and Applications     
Th. Nov 30Veloso Multi-Agent Systems: Layered Learning     
Tu. Dec 5Veloso Multi-Robot Systems with Global Perception     
Th. Dec 7Veloso Fully Autonomous Multi-Robot Systems   HW6 
Tu. Dec 12Jensen/Hiyakumoto Review Session - sample problem solutions part1, part2     
Th. Dec 14  FINAL EXAM: 8:30am to 11:30am, rooms DH1211 & DH1212     

Note: Recitations will be scheduled on an as-needed basis (e.g. a few days before each homework is due, or to review a difficult topic if there is sufficient demand as judged at the end of class).

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Last modified: Tue Dec 4 09:53:03 EST 2001
L. Hiyakumoto