CS561-FoundationsofArtificialIntelligence-SvenKoenig

webmaster: Sven Koenig

Schedule

Class Schedule

Overview

  • Aug 25 Discussion of syllabus and class rules
  • Aug 27 Overview of artificial intelligence and intelligent agents (chapters 1 and 2) [ pdf ]

Search and Planning

  • Sep 01 Encoding planning problems (chapter 11) [ pdf, handout ]
  • Sep 03 State spaces and uninformed search (chapter 3) [ pdf ]
  • Sep 08 Informed search (chapter 4) [ pdf ]
  • Sep 10 Search-based planning (chapter 11) [ pdf ]
  • Sep 11 First Drop Date
  • Sep 15 Partial-order planning (chapter 11) [ pdf ]
  • Sep 17 Hillclimbing, simulated annealing, genetic algorithms (chapter 4) [ pdf ]
  • Sep 22 Planning with propositional logic (including constraint satisfaction) (chapters 5, 7 and 11) [ pdf ]
  • Sep 24 Review
  • Sep 29 First Midterm

Machine Learning

  • Oct 01 Perceptrons and neural networks (chapter 20) [ pdf ]
  • Oct 06 Perceptrons and neural networks (chapter 20) [ pdf1 and pdf2 ]
    There is a typo in pdf1: g'(x) = e^(-x)/(1+e^(-x))^2.
  • Oct 08 Decision trees (chapter 18) [ pdf ]

Game Playing

  • Oct 13 Minimax technique (chapter 6) [ pdf ]
  • Oct 15 Alpha-beta technique (chapter 6) [ pdf ]

Probabilistic Search and Planning

  • Oct 20 Probabilities (chapter 13) [ pdf ]
  • Oct 22 Bayesian networks (chapter 14) [ pdf ]
  • Oct 27 Bayesian networks (chapter 14) [ pdf ]
  • Oct 29 Review
  • Nov 03 Second Midterm
  • Nov 05 Value of information (chapter 16) [ pdf ][ Lecture slides from XiaoMing ]
  • Nov 10 Markov decision processes - value and policy iteration (chapters 17 and 21) [ pdf ]
  • Nov 12 Markov decision processes - discounting and reinforcement learning (chapter 17 and 21) [ pdf ]
  • Nov 13 Second Drop Date

Knowledge Representation and Reasoning

  • Nov 17 First-order logic (chapter 8) [ pdf, handout ]
  • Nov 19 Reasoning with logic (chapter 7) [ pdf ]
  • Nov 24 Reasoning with logic (chapter 7) [ pdf ]
  • Nov 26 Thanksgiving Holiday
  • Dec 01 Frames, semantic networks and spreading activation (chapter 10) [ pdf ]
  • Dec 03 Review
  • Dec 10 Final for sections 30079 & 30080
  • Dec 15 Final for section 30219

Homework Schedule

Homework assignments are self-tests. 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 01 HW1 Encoding planning problems
  • Sep 08 HW2 Search
  • Sep 15 HW3 Partial-order planning
  • Oct 06 HW4 Neural networks
  • Oct 13 HW5 Decision trees
  • Oct 20 HW6 Game playing
  • Oct 27 HW7 Probabilities and Bayesian networks
  • Nov 10 HW8 Value of information
  • Nov 17 HW9 Markov decision processes
  • Nov 24 HW10 First-order logic

Project Schedule

The project schedule does not include the automatic grace period. For example, project 1 counts as handed in late (resulting in zero credit) only if you do not manage to hand it in by 11:59pm on Sep 26. However, please note that the project deadlines are a short time before the midterms. Thus, making use of the automatic grace periods takes away from your exam preparation time.

  • Sep 10 Project 1 out
  • Sep 24 Project 1 due (anytime, up to 11:59pm)
  • Oct 8 Project 2 out
  • Oct 22 Project 2 due (anytime, up to 11:59pm)
  • Nov 12 Project 3 out
  • Dec 01 Project 3 due (anytime, up to 11:59pm)

Powered by PmWiki