| Week | Date | Topic/Read Before Class | Notes | Homework |
| 1 | M, 08/31 | Ch. 01. Introduction | Ch. 01 - Introduction
full page pdf, ps, |
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| W, 09/02 | Ch. 02 - Intelligent Agents | Ch. 02 - Intelligent Agents
full page pdf, ps, |
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| F, 09/04 | Ch. 03 - Problem Solving by Searching
goal-driven agents formulating search problems basic search algorithm blind search breadth-first search uniform cost search depth-first-search depth-limited-search iterative deepening search iterative broadening search |
Ch. 03 - Problem Solving by Searching full page slides pdf |
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| 2 | M, 09/07 | Labor day: no class | ||
| W, 09/09 | ||||
| F, 09/11 | K- day: no class | |||
| 3 | M, 09/14 | Ch. 04 - Informed search and exploration
Best first search Greedy search A* search Admissible heuristics A* is optimal Properties of heuristics Admissible heuristics Consistent heuristics Heuristic dominance IDA* search IDA* is optimal Performance of IDA* Designing heuristics Relaxed problems Minimum Spanning tree heuristic for TSP Iterative improvement algorithms Hill climbing Simulated annealing Tabu search, stochastic hill climbing, genetic algorithms, ant colony optimization |
Ch. 04 - Informed Search and Exploration full page slides pdf |
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| W, 09/16 | hw1: search
Due: Oct 12, 2009 |
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| F, 09/18 | no class | |||
| 4 | M, 09/21 |
Ch. 05 - Constraint Satisfaction Problems
Definition, example Backtracking search Heuristics for backtracking search Arc consistency Tree structured CSPs Iterative algorithms for CSPs |
Ch. 05 - CSP
full page slides pdf |
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| W, 09/23 | ||||
| F, 09/25 | ||||
| 5 | M, 09/28 |
Temporal Constraint Networks
(Addition to Chapter 5) The interval algebra (IA) Definition, examples Path consistency in CSPs Path consistency in IA Qualitative Path Consistency (QPC) algorithm The point algebra (PA) Definition, examples Composition in PA Properties of PA algorithms Simple Temporal Networks (STNs) Definition, examples Floyd-Warshall Algorithm Properties of STN/TCSP algorithms |
Ch. 05b- Temporal CSP
full page pdf, ps, 4 per page ps IA example (pdf) STN example (pdf) |
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| W, 09/30 | ||||
| F, 10/02 | ||||
| 6 | M, 10/05 |
Ch. 11 - Planning
Planning vs. search State space search Operator description POP algorithm Plan structure The search algorithm Closing open conditions Resolving threats Properties of POP Heuristics for POP Additional examples |
Ch. 11 - Planning
full page pdf, ps, 4 per page ps |
W, 10/07 |
| F, 10/09 | ||||
| 7 | M,10/12 |
Ch. 11 - Planning
Graphplan algorithm Planning graphs Mutexes Expanding the graph Searching for a solution Properties of planning graphs Using planning graphs as heuristics |
Ch. 11b - Planning Graphs
full page pdf, ps, 4 per page ps |
hw2: CSPs
Due: Oct 19, 2009 |
| W, 10/14 | ||||
| F, 10/16 |
Ch. 11 - Planning
The Satplan algorithm Boolean satisfiability (SAT) Satplan architecture Simplifying CNF formulas Building CNF formulas for planning problems Frame axioms (full, explanatory) Properties of frame axioms Symbol splitting SAT solving algorithms (DPLL, WALKSAT, GSAT) |
Ch. 11c - Satplan
full page pdf, ps, 4 per page ps |
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| 8 | M, 10/19 |
Ch. 16 - Making Simple Decisions
Maximizing expected utility Influence diagrams Coming up with utility numbers Stochastic dominance Value of information |
Ch. 16 - decision making
full page pdf, ps, 4 per page ps |
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| W, 10/21 | Midterm exam (take home)
Handed out: Wednesday,10/21/09 at 12:55pm Due: Friday, 10/23/09 at 12:05pm |
Good luck! | ||
| F, 10/23 | hw3: research paper
Due: Nov. 9, 2009 |
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| 9 | M, 10/26 |
Ch. 17 - Making Complex Decisions
MDP problems Bellman updates Solving MDPs using value iteration Solving MDPs using policy iteration The RTDP algorithm |
Ch. 17 - MDPs
full page pdf, ps, 4 per page ps |
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| W, 10/28 | ||||
| F, 10/30 | ||||
| 10 | M, 11/02 |
Ch. 13 - Uncertainty
Probability basics Random variables Prior probability Conditional probability Inference by enumeration Normalization, the α notation Independence Conditional independence Bayes' rule The Wumpus world |
Ch. 13 - uncertainty
full page pdf, 6 per page pdf |
|
| W, 11/04 | ||||
| F, 11/06 | ||||
| 11 | M, 11/09 |
Ch. 14 - Probabilistic Reasoning
Section 14.1 Representing Knowledge in an Uncertain Domain Section 14.2 The Semantics of Bayesian Networks Section 14.3 Efficient Representation of Conditional Distributions |
Ch. 14a - Sections 14.1 - 14.3
full page pdf, 6 per page pdf |
hw4: probabilistic reasoning
Due: Nov. 16, 2009 |
| W, 11/11 |
Ch. 14 - Probabilistic Reasoning
Section 14.4 Exact Inference in Bayesian Networks Section 14.5 Approximate Inference in Bayesian Networks |
Ch. 14b - Sections 14.4 - 14.5
full page pdf, 6 per page pdf |
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| F, 11/13 | Research projects | TONAE ICDMA |
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| 12 | M, 11/16 |
Ch. 12 - Planning and acting in the real world
Section 12.1 - Planning with time and resources Section 12.2 - Hierarchical Task Network Planning Section 12.3 - Planning and Acting in Nondeterministic Domains Section 12.4 - Conditional Planning Section 12.5 Execution Monitoring and Replanning Section 12.6 Continuous Planning (Section 12.7 MultiAgent Planning) |
Ch. 12a - time and resources
full page pdf, ps, 4 per page ps Ch. 12b - HTN full page pdf, ps, 4 per page ps Ch. 12c - Conditional planning full page pdf, ps, 4 per page ps Ch. 12d - replan full page pdf, ps, 4 per page ps Ch. 12e - continuous full page pdf, ps, 4 per page ps |
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| W, 11/18 | Final exam (take home)
Handed out: Wednesday, 11/18/09 at 12:55pm Due: Friday, 11/20/09 at 12:05pm |
Good luck! | ||
| F, 11/20 | Student presentations:
Congyi's presentation |
hw5: Overview Research Papers
Due: Dec. 11, 2009 |
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| - | M, 11/23 | Thanksgiving recess | ||
| 13 | M, 11/30 | Student presentations:
Kit's presentation Dean's presentation |
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| W, 12/02 | Student presentations:
Antti's presentation Reid's presentation |
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| F, 12/04 | Student presentations:
Yi's presentation Xiao's presentation |
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| 14 | M, 12/07 | Student presentations:
Bin's presentation Jun's presentation |
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| W, 12/09 | Student presentations:
Ryan's presentation Neelu's presentation |
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| F, 12/11 | Student presentations:
Paul's presentation Eric's presentation |
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| Finals | No exam during finals week |