Introduction to Artificial Intelligence

Lecture Topic
| Readings in AIMA | Assignments | ||

Aug | 30 | Introduction, history | Chapter 1 | A0 (Lisp) |

Sep | 1 | Intelligent agents | Chapter 2 | |

6 | Problem solving, uninformed search | Chapter 3 | ||

8 | A* search and heuristic functions | Chapter 4.1-4.2 | A0 due, A1 (Search) | |

13 | Local and online search | Chapter 4.3-4.5 | ||

15 | Constraint satisfaction | Chapter 5.1-5.2 | ||

20 | Constraint satisfaction contd. | Chapter 5.3-5.4 | A1 due, A2 (Search, CSPs) | |

22 | Game-playing | Chapter 6 | ||

27 | Logical agents; propositional logic | Chapter 7.1-7.4 | ||

29 | Inference in propositional logic | Chapter 7.5-7.7 | ||

Oct | 4 | First-order logic | Chapter 8.1-8.3 | |

6 | Actions in first-order logic; inference | Chapter 10.3, Chapter 9.1-9.2 | A2 due (10/9), A3 (Logic) | |

11 | Inference contd., logic programming | Chapter 9.3-9.5 | ||

13 | Planning | Chapter 11.1-11.3 | A3 due (10/16) | |

18 | Midterm
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20 | Probability theory | Chapter 13 | ||

25 | Bayesian networks | Chapter 14.1-14.3 | A4 (Probability, Bayes nets) | |

27 | Inference in Bayesian networks | Chapter 14.4-14.5 | ||

Nov | 1 | Temporal probability models, speech recognition | Chapter 15.1-15.6 | |

3 | Rational decisions | Chapter 16.1-16.3, 16.4-16.6 | A4 due (11/4), A5 (Bayes net inference) | |

8 | Sequential decisions | Chapter 17.1-17.4 | ||

10 | Decision tree learning | Chapter 18.1-18.3 | ||

15 | Statistical learning | Chapter 20.1-20.3 | ||

17 | Neural networks | Chapter 20.5 | ||

22 | Reinforcement learning | Chapter 21.1-21.4 | ||

24 | Thanksgiving
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29 | Natural language communication and syntax | Chapter 22.1-22.3 | A5 part 2 due (11/28), A6 (Reinforcement learning) | |

Dec | 1 | Natural language semantics | Chapter 22.5-22.7 | |

6 | Robotics | Chapter 24 | ||

8 | Philosophical issues | Chapter 25.1-25.4 | A6 due (12/12) | |

19 | Final (12.30pm - 3.30pm)
| Location TBD |