Lecture notes will be linked to this web page, in PDF format. The reader for PDF files is available free from Adobe for UNIX, Apple Macintosh, and Windows.

Lec. |
Date |
Topic |
Readings |
Slides |
To-do (TENTATIVE DATES! Check frequently.) |

Introduction |
RN, Chapter 1 & 2 | Slides | |||

Search (uninformed) |
RN, Chapter 3 | Slides | |||

Search (informed) |
RN, Chapter 3 | Slides | |||

Search (optimization) |
RN, Section 4.1 | Slides | Homework 1 available now. Sample base code (in python, change the extension to .py to run). Sample input file. | ||

Search (under uncertainty) |
RN, Sec. 4.2-4.5 | Slides | |||

Constraint satisfaction |
RN, Chapter 6 | Slides | |||

Game playing (Minimax) |
RN, Chapter 5 | Slides | Homework 1 due (next day). Now available: Homework 1 solution set | ||

Game playing (Monte-Carlo search trees) |
RN, Chapter 5 | Slides | |||

Logical reasoning (propositional logic) |
RN, Chapter 7 | Slides | Homework 2 with modified definition of Stop operator for Q4. | ||

Logical reasoning (first-order logic) |
RN, Chapters 8, 9 | Slides | |||

Sequential logical reasoning (classical planning) |
RN, Chapter 10 | Slides | Practice questions with some solutions. Old midterm. | ||

Probabilistic reasoning (basics) |
RN, Chapter 13 | Slides | Homework 2 due (next day). Homework 2 solution set | ||

Midterm Exam |
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Probabilistic reasoning (Bayesian networks) |
RN, Sec. 14.1, 14.2, 14.4 | Slides | Project specification (ver.2), code description and project code repository are now posted. | ||

Probabilistic reasoning (Bayesian networks cont'd) |
RN, Sec. 14.1, 14.2, 14.4 | Slides | Homework 3 available. | ||

Learning probabilistic models with complete data |
RN, Sec. 20.1-20.2 (up to p.719) | Slides | |||

Study week. |
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Study week. |
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Learning probabilistic models with missing data |
RN, Sec. 20.3 | Slides | Homework 3 due (next day). Homework 3 solution set (updated Mar.18) | ||

Reasoning with temporal probabilistic models (HMMs) |
RN, Sec. 15.1-15.3 | Slides | Homework 4 available. Additional notes on soft EM | ||

Learning temporal probabilistic models (Baum-Welch) |
RN, Sec. 20.3 | Slides | |||

Reasoning with utilities |
RN, Chapter 16 | Slides | |||

Learning utilities from exploration (Bandits) |
RN, Sec. 21.3 | Slides | Homework 4 due (next day). Homework 4 solution set | ||

Sequential reasoning (Markov Decision Processes) |
RN, Sec. 17.1 - 17.3 | Slides | Homework 5 available. | ||

Sequential reasoning (Markov Decision Processes, cont'd) |
Slides | ||||

Learning sequential decisions (Reinforcement Learning) |
RN, Chapter 21 | Slides | Homework 5 due (next day). Homework 5 solution set | ||

Reasoning under uncertainty (POMDPs) and/or with multiple agents |
RN, Sec. 17.4-5 | Slides | |||

AI: Present and Future. |
RN, Chapters 26 and 27 | Slides | Project due (Update: due next day, Apr.11, 11:59pm). Written report evaluation form. |