COMP 4106 Lecture Notes - Lecture 4: Search Algorithm, Tree Traversal, The Algorithm

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Restart the searching, doing it again, looking ahead a certain number of levels (ex. Want to move to have the bigger advantage: choose move to position with highest mini-max value = best achievable payoff against best play, example: 2-ply game, mini-max for nim. Label nodes as min or max, alternating for each level: define utility function (payoff function), do full search on tree, expand all nodes until game is over for each branch. Start at the leaf nodes of the main search, and try to solve this problem. In chess, quiescence searches usually include all capture moves, so that tactical exchanges don"t mess up the evaluation. If you know that the le(cid:448)el a(cid:271)o(cid:448)e (cid:449)o(cid:374)"t (cid:272)hoose (cid:455)our (cid:271)ra(cid:374)(cid:272)h (cid:271)e(cid:272)ause (cid:455)ou ha(cid:448)e alread(cid:455) found a value along one of your sub-branches that is too good, stop looking at other sub-(cid:271)ra(cid:374)(cid:272)hes that ha(cid:448)e(cid:374)"t (cid:271)ee(cid:374) looked at (cid:455)et.

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