This shows you the differences between two versions of the page.
Both sides previous revision Previous revision | Next revision Both sides next revision | ||
start [2020/08/26 13:50] anderson [Announcements] |
start [2020/08/27 13:54] 127.0.0.1 external edit |
||
---|---|---|---|
Line 3: | Line 3: | ||
===== Announcements ===== | ===== Announcements ===== | ||
+ | The live lecture is in the MS Teams meeting [[https:// | ||
Lecture and office hour videos are available from the Home page of our | Lecture and office hour videos are available from the Home page of our | ||
Line 24: | Line 25: | ||
|< 100% 18% 20% 22% 20% 20% >| | |< 100% 18% 20% 22% 20% 20% >| | ||
^ 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 | 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 classes, sorting, numpy arrays. | + | | 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, effective branching factor.\\ Local search and optimization. | ||
| Week 5:\\ Sept 21 - Sept 25 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. | | Week 5:\\ Sept 21 - Sept 25 | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. |