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start [2017/08/23 08:52] anderson [October] |
start [2018/08/26 23:10] anderson [August] |
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- | Lecture videos are available from the Canvas site (in the menu on the left) by selecting [[https:// | + | Lecture videos are available from the Canvas site (in the menu on the left) by selecting [[https:// |
- | /* | + | To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: |
- | are available at this [[https://echo.colostate.edu/ess/portal/ | + | |
- | */ | + | export PATH=/usr/local/anaconda/bin:$PATH |
+ | |||
+ | |||
+ | This is a tentative schedule of CS440 topics for Fall, 2018. This will be updated during the summer and as the fall semester continues. | ||
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^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 1:\\ Aug 21 - Aug 25 | What is AI? Promises and fears.\\ Python review.\\ Problem-Solving Agents. | + | | Week 1:\\ Aug 20 - Aug 24 | What is AI? Promises and fears.\\ Python review.\\ Problem-Solving Agents. |
- | | Week 2:\\ Aug 28 - Sept 1 | + | | Week 2:\\ Aug 27 - Aug 31 | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. |
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|< 100% 10% 20% 30% 20% 20% >| | |< 100% 10% 20% 30% 20% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 3:\\ Sept 4 - Sept 8 | Informed search. A* search. Python classes, sorting, numpy arrays. | + | | Week 3:\\ Sept 4 - Sept 7\\ No class on the Sept 3 University Holiday |
- | | Week 4:\\ Sept 11 - Sept 15 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. | + | | Week 4:\\ Sept 10 - Sept 14 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. |
- | | Week 5:\\ Sept 18 - Sept 22 | Adversarial search. Minimax. Alpha-beta pruning. | + | | Week 5:\\ Sept 17 - Sept 21 | Adversarial search. Minimax. Alpha-beta pruning. |
- | | Week 6:\\ Sept 25 - Sept 29 | Stochastic games. Expectimax. | | Sections 5.5 - 5.6 | | + | | Week 6:\\ Sept 24 - Sept 28 | Negamax, with pruning. | [[http:// |
===== October ===== | ===== October ===== | ||
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|< 100% 10% 20% 30% 20% 20% >| | |< 100% 10% 20% 30% 20% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 7:\\ Oct 2 - Oct 6 | Introduction to Reinforcement Learning. | + | | Week 7:\\ Oct 2 - Oct 6 | Introduction to Reinforcement Learning. |
- | | Week 8:\\ Oct 9 - Oct 13 | Constraint satisfaction. Min-conflicts | + | | Week 8:\\ Oct 9 - Oct 13 | Reinforcement Learning for Two-Player Games.\\ Introduction to Neural Networks |
- | | Week 9:\\ Oct 16 - Oct 20 | Propositional and First-Order Logic. Introduction to Prolog. | | Chapters 7, 8, 9 | | + | | Week 9:\\ Oct 16 - Oct 20 | More Neural Networks |
- | | Week 10:\\ Oct 23 - Oct 27 | | | | | + | | Week 10:\\ Oct 23 - Oct 27 | Introduction to Classification. Bayes Rule. Generative versus Discriminative. Linear Logistic Regression. |
===== November ===== | ===== November ===== | ||
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^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 11:\\ Oct 30 - Nov 3 | + | | Week 11:\\ Oct 30 - Nov 2 |
- | | Week 12:\\ Nov 6 - Nov 10 | + | | Week 12:\\ Nov 5 - Nov 9 |
- | | Week 13:\\ Nov 13 - Nov 17 | + | | Week 13:\\ Nov 12 - Nov 16 |
- | | Nov 20 - Nov 24 | + | | Nov 19 - Nov 23 |
- | | Week 14:\\ Nov 27 - Dec 1 | + | | Week 14:\\ Nov 26 - Nov 30 |
===== December ===== | ===== December ===== | ||
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^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 15:\\ Dec 4 - Dec 8 | + | | Week 15:\\ Dec 3 - Dec 7 |
- | | Finals | + | | Final Exam Week:\\ Dec 10 - Dec 14 |