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start [2020/08/28 08:52] anderson [Announcements] |
start [2020/09/22 11:55] anderson [September] |
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- | ====== Schedule ====== | + | ===== Schedule ====== |
===== Announcements ===== | ===== Announcements ===== | ||
Links to live MS Teams events: | Links to live MS Teams events: | ||
- | * Lectures: | + | * Lectures: [[https:// |
- | * Office hours: Apoorv [[https:// | + | * Office hours: Apoorv [[https:// |
* Office hours: Chaitanya [[https:// | * Office hours: Chaitanya [[https:// | ||
* Office hours: Chuck [[https:// | * Office hours: Chuck [[https:// | ||
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^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 2:\\ Aug 31 - Sept 4 | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. | + | | Week 2:\\ Aug 31 - Sept 4 | Help with A1.\\ Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. |
- | | Week 3:\\ Sept 7 - Sept 11 | Informed search. A* search. Python | + | | Week 3:\\ Sept 7 - Sept 11 | Informed search. A* search. Python classes, sorting, numpy arrays. |
- | | Week 4:\\ Sept 14 - Sept 18 | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. | + | | Week 4:\\ Sept 14 - Sept 18 | A* optimality, admissible heuristics |
- | | Week 5:\\ Sept 21 - Sept 25 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. | + | | Week 5:\\ Sept 21 - Sept 25 |
| Week 6:\\ Sept 28 - Oct 2 | Negamax, with pruning. Introduction to Reinforcement Learning. | | Week 6:\\ Sept 28 - Oct 2 | Negamax, with pruning. Introduction to Reinforcement Learning. | ||