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 |

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: (new version with correction posted Jan.19 9:45am, see yellow highlight on p.2) Instructions Sample code (save using extension .py instead of .txt) Readme file. |
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Constraint satisfaction |
RN, Chapter 6 | Slides | |||

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

Game playing (Minimax) |
RN, Chapter 5 | Slides | Homework 1 due. | ||

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

Logical reasoning (propositional logic) |
RN, Chapter 7 | Slides | Homework 2: Instructions Change log: Minor modications to Q2 logical statements shown in yellow (Feb.5, 9:53) These are optional, you can use the original formulation, though this may yield a different solution; we will accept both. Base code Change log: Fixed solve_sudoku() call in sudoku.py (Feb.3) New error message for the human player (Feb.4, 15:14) | ||

Logical reasoning (first-order logic) |
RN, Chapters 8, 9 | Slides | Project code and instructions now available (Version 2 posted Mar.11, deals with infinite moves). |
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Sequential logical reasoning (classical planning) |
RN, Chapter 10 | Slides | |||

Probabilistic reasoning (basics) |
RN, Chapter 13 | Slides | Homework 2 due next day (Feb.12). | ||

Midterm Exam (CONFIRMED) |
Practice questions with some solutions. Old midterm. | ||||

Probabilistic reasoning (Bayesian networks) |
RN, Sec. 14.1, 14.2, 14.4 | Slides | |||

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

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. | ||

Reasoning with temporal probabilistic models (HMMs) |
RN, Sec. 15.1-15.3 | Slides | Homework 4: Instructions (Ignore the last question.) | ||

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

Learning from examples |
RN, Chapter 18 | Slides | |||

Reasoning with utilities |
RN, Chapter 16 | Slides | Homework 4 due. | ||

Learning utilities from exploration (Bandits) |
RN, Sec. 21.3 | Slides | |||

Sequential reasoning (Markov Decision Processes) |
RN, Sec. 17.1 - 17.3 | Slides | Final project code due. Report due on Apr.1. See evaluation form. |
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Sequential reasoning (Markov Decision Processes, cont'd) |
Slides | Homework 5: Instructions | |||

Easter Monday |
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Learning sequential decisions (Reinforcement Learning) |
RN, Chapter 21 | Slides | Tutorial on problem solving with probabilistic models (Today: 4-6pm, MC103) |
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Reasoning under uncertainty (POMDPs) / AI present and future |
RN, Sec. 17.4-5, Ch. 26, 27 | Slides | Homework 5 due. | ||

Final Exam (9am-12pm) |