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start [2018/08/20 10:36] anderson [August] |
start [2018/08/29 14:14] anderson [September] |
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===== Announcements ===== | ===== Announcements ===== | ||
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- | Sept 7: Assignment 2 is now complete. | + | Lecture videos are available from the Canvas site (in the menu on the left) by selecting [[https:// |
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- | Aug 31: Assignment 1 now includes another example. | + | |
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- | 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: | To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: | ||
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export PATH=/ | export 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. | 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 20 - Aug 24 | 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 27 - Aug 31 | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. | + | | 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 7\\ No class on the Sept 3 University Holiday | + | | Week 3:\\ Sept 4 - Sept 7\\ No class on the Sept 3 (University Holiday) and Sept 5 (instructor traveling) |
- | | Week 4:\\ Sept 10 - Sept 14 | 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 17 - Sept 21 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. | | Week 5:\\ Sept 17 - Sept 21 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. | ||
| Week 6:\\ Sept 24 - Sept 28 | Negamax, with pruning. | [[http:// | | Week 6:\\ Sept 24 - Sept 28 | Negamax, with pruning. | [[http:// | ||
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^ 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 | Reinforcement Learning for Two-Player Games.\\ Introduction to Neural Networks | | Week 8:\\ Oct 9 - Oct 13 | Reinforcement Learning for Two-Player Games.\\ Introduction to Neural Networks | ||
| Week 9:\\ Oct 16 - Oct 20 | More Neural Networks | | Week 9:\\ Oct 16 - Oct 20 | More Neural Networks |