Adversarial Search Chapter 6 Section 1 – 4 Games vs. search problems "Unpredictable" opponent specifying a move for every possible opponent reply Time limits unlikely to find goal, must approximate Solutions Search problems: a path Games: a strategy But how?
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Section 1 – 4
Suppose we have 100 secs, explore 104 nodes/sec106nodes per move
e.g., depth limit (perhaps add quiescence search)
Explore nonquiescent positions further until quiescence
= estimated desirability of position
Eval(s) = w1 f1(s) + w2 f2(s) + … + wn fn(s)
f1(s) = (number of white queens) – (number of black queens), etc.
MinimaxCutoff is identical to MinimaxValue except
Does it work in practice?
bm = 106, b=35 m=4
4-step lookahead is a hopeless chess player!