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start [2017/09/17 12:33] anderson [September] |
start [2017/10/11 21:06] anderson [October] |
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^ 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 8 | Informed search. A* search. Python classes, sorting, numpy arrays. |
- | | Week 4:\\ Sept 11 - Sept 15 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. | + | | Week 4:\\ Sept 11 - Sept 15 | 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 18 - Sept 22 | Adversarial search. Minimax. Alpha-beta pruning. |
- | | Week 6:\\ Sept 25 - Sept 29 | + | | Week 6:\\ Sept 25 - Sept 29 |
===== 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 | | + | | Week 7:\\ Oct 2 - Oct 6 | Introduction to Reinforcement Learning. |
- | | Week 8:\\ Oct 9 - Oct 13 | | + | | Week 8:\\ Oct 9 - Oct 13 | Reinforcement Learning for Two-Player Games.\\ Introduction to Neural Networks |
| Week 9:\\ Oct 16 - Oct 20 | | | Week 9:\\ Oct 16 - Oct 20 | | ||
- | | Week 10:\\ Oct 23 - Oct 27 | Introduction to Reinforcement Learning. | + | | Week 10:\\ Oct 23 - Oct 27 | | | |
===== November ===== | ===== November ===== |