Lecture Schedule:

Overview

• Aug 27 overview and intelligent agents (chapters 1 and 2) [pdf]

Machine Learning

• Aug 29 decision trees (chapter 18) [pdf]
• Sep  3 Labor day (no class)
• Sep  5 neural networks (chapter 20) [pdf]

Search

• Sep 10 uninformed search (chapter 3) [pdf]
• Sep 12 informed search (chapter 4) [pdf]
• Sep 14 drop day without a mark of W (no class)
• Sep 17 hillclimbing, simulated annealing, genetic algorithms (chapter 4) [pdf]

Planning

• Sep 19 encoding planning problems (chapter 11) [pdf]
• Sep 24 guest lecture [pdf]
• Sep 26 guest lecture [pdf]
• Oct  1 search-based planning (chapter 11) [pdf] [STRIPS pdf]
• Oct  3 partial-order planning (chapter 11) [pdf]
• Oct  8 midterm [practice pdf]

Game Playing

• Oct 10 minimax technique (chapter 6) [pdf]
• Oct 15 alpha-beta techniques (chapter 6) [pdf]

Knowledge Representation and Reasoning

• Oct 17 propositional logic (chapter 7) [pdf]
• Oct 22 first-order logic (chapter 8) [pdf] [Logic pdf]
• Oct 24 reasoning with logic (chapter 7) [pdf]
• Oct 29 guest lecture [pdf]
• Oct 31 guest lecture [pdf]
• Nov  5 more reasoning with logic (chapter 7) [pdf]
• Nov  7 frames, semantic networks and spreading activation, scripts (chapter 10) [pdf]
• Nov 12 planning with logic (including constraint satisfaction) (chapters 11 and 5) [pdf]

Probabilistic Search, Reasoning, and Machine Learning

• Nov 14 probabilities (chapter 13) [pdf]
• Nov 16 drop day with mark of W (no class)
• Nov 19 midterm [practice midterm]
• Nov 21 Bayesian networks (chapter 14) [pdf]
• Nov 26 Bayesian networks (chapter 14) [pdf]
• Nov 28 Markov decision processes and reinforcement learning (chapters 17 and 21) [pdf]
• Dec  3 Markov decision processes and reinforcement learning (chapters 17 and 21) [pdf] [value info slides] [value info pdf]
• Dec  5 Markov decision processes and reinforcement learning (chapters 17 and 21) [pdf]
• Dec  7 classes end (no class)
• Dec 14 final [practice final]

Homework Schedule:

Homeworks are selftests. You do not submit your solutions and you do not get credit for them. However, they are excellent tests whether you understood the material and will help you to prepare for the exams. We will post the solutions one week after we posted the homework.

• Sep  5 HW decision trees out
• Sep 12 HW neural networks out
• Sep 19 HW search out
• Sep 26 HW encoding planning problems out
• Oct  3 HW partial-order planning out
• Oct 17 HW game playing out
• Oct 24 HW first-order logic out
• Nov 21 HW probabilities and Bayesian networks out
• Nov 28 HW Markov decision processes out

Project Schedule:

• Sep 12 project 1 out
• Oct  4 project 1 due (anytime on Oct 4, up to midnight)
• Oct 10 project 2 out
• Oct 24 project 2 due (anytime on Oct 24, up to midnight)
• Nov  7 project 3 out
• Nov 21 project 3 due (anytime on Nov 21, up to midnight)