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start [2017/08/23 08:53] anderson [October] |
start [2020/08/26 13:50] anderson [Announcements] |
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- | Lecture videos are available from the Canvas site (in the menu on the left) by selecting | + | Lecture |
+ | [[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, 2020. This will be updated during the summer and as the fall semester continues. | ||
===== August ===== | ===== August ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ 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 24 - Aug 28 | What is AI? Promises and fears.\\ Python review.\\ Problem-Solving Agents. |
- | | Week 2:\\ Aug 28 - Sept 1 | + | |
===== September ===== | ===== September ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
- | ^ Week ^ Topic ^ Material | + | ^ Week ^ Topic ^ Material |
- | | Week 3:\\ Sept 4 - Sept 8 | Informed search. A* search. Python classes, sorting, numpy arrays. | + | | Week 2:\\ Aug 31 - Sept 4 | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. |
- | | Week 4:\\ Sept 11 - Sept 15 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. | + | | Week 3:\\ Sept 7 - Sept 11 | Informed search. A* search. Python classes, sorting, numpy arrays. |
- | | Week 5:\\ Sept 18 - Sept 22 | Adversarial search. Minimax. Alpha-beta pruning. | + | | Week 4:\\ Sept 14 - Sept 18 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. |
- | | Week 6:\\ Sept 25 - Sept 29 | Stochastic games. Expectimax. | | Sections 5.5 - 5.6 | | + | | Week 5:\\ Sept 21 - Sept 25 | Adversarial search. Minimax. Alpha-beta pruning. |
+ | | Week 6:\\ Sept 28 - Oct 2 | Negamax, with pruning. Introduction to Reinforcement Learning. | <!-- [[http:// | ||
===== October ===== | ===== October ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 7:\\ Oct 2 - Oct 6 | + | | Week 7:\\ Oct 5 - Oct 9 | Reinforcement Learning |
- | | Week 8:\\ Oct 9 - Oct 13 | + | | Week 8:\\ Oct 12 - Oct 16 |
- | | Week 9:\\ Oct 16 - Oct 20 | + | | Week 9:\\ Oct 19 - Oct 23 |
- | | Week 10:\\ Oct 23 - Oct 27 | + | | Week 10:\\ Oct 26 - Oct 30 |
===== November ===== | ===== November ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 11:\\ Oct 30 - Nov 3 | + | | Week 11:\\ Nov 2 - Nov 6 |
- | | Week 12:\\ Nov 6 - Nov 10 | + | | Week 12:\\ Nov 9 - Nov 13 |
- | | Week 13:\\ Nov 13 - Nov 17 | + | | Week 13:\\ Nov 16 - Nov 20 |
- | | Nov 20 - Nov 24 | + | | Nov 23 - Nov 27 |
- | | Week 14:\\ Nov 27 - Dec 1 | + | |
===== December ===== | ===== December ===== | ||
- | |< 100% 10% 20% 30% 20% 20% >| | + | |< 100% 18% 20% 22% 20% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 15:\\ Dec 4 - Dec 8 | + | | Week 14:\\ Nov 30 - Dec 4 |
- | | Finals | + | | Week 15:\\ Dec 7 - Dec 11 |
+ | | Final Exam Week:\\ Dec 14 - Dec 18 | | | | | | ||
+ | |||