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OMSCS-AI (Thad: (Game Playing (Toolbox
MinMax
Alpha pruning
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OMSCS-AI
Thad:
- The difference between PR, AI and DM is subtle
- A* is a popular interview question
Game Playing
Toolbox
- MinMax
- Alpha pruning
- Adversrial search
- Iterative deepening
- Symmetry, good opening book and
occupy center, relection for the old game
- MAXN tree，感觉自己时刻在上演《回到未来》以解题
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Understand the Isolation game and the tree representation of search space, it was fun:smile:
The controdiction between searching to level2 and level3 is impressive
Depth is required
quiescent search?
Iterative deeping-Keep current result and search deeper
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Alpha-Beta Prune: using DFS
Pruning, Korsh 论文说总体和有上界每个有下界就可以 AB Pruning
Confusion
- What is the exact level number?
- Theortiical analysis of alpha-beta pruning
Simulated Annealing
Try the silly thing first, then optimize it
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Peter:
Search
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Graph Search
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Comparison Between search algorithms, optimal and completeness
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A*, greedy and optimal by g+h, best estimated total path cost first but how to guarantee correctness? Correct if h(s ) <(< or <=) true_cost(s)
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