Hill-Climbing Search and Dynamic Programming:. Heuristics. Motivations. If a problem has polynomial-time solutions, traditional programming techniques are used to implement the solutions. AI problems, however, are exponential in nature, e.g., chess, traveling salesman.
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Hill-Climbing Search and Dynamic Programming:
1st ply, 9 choices
2nd ply, 8 choices
Each path from root to leaf is a possible game.
At most 9! possible games.
Combinatorial! not just
State space reduced by symmetry
rotate and/or flip
Heuristic: Most wining opportunities
Heuristically reduced state space
Strongest opening move
is the center.
winning opportunities for x
2 possible replies for o
after symmetry is considered
Use same heuristic until game over.
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Saccharomyces cerevisiae TCP1-beta gene
1 gatcctccat atacaacggt atctccacct caggtttaga tctcaacaac gaaccattg
61 ccgacatgag acagttaggt atcgtcgaga gttacaagct aaaacgagca tagtcagct
121 ctgcatctga agccgctgaa gttctactaa gggtggataa catcatccgt caagaccaa
181 gaaccgccaa tagacaacat atgtaacata tttaggatat acctcgaaaa aataaaccg
241 ccacactgtc attattataa ttagaaacag aacgcaaaaa ttatccacta ataattcaa
4921 ttttcagtgt tagattgctc taattctttg agctgttctc tcagctcctc atatttttct 4981 tgccatgact cagattctaa ttttaagcta ttcaatttct ctttgatc
Base counts: 1510 a’s, 1074 c’s, 835 g’s, and 1609 t’s
Insert, cost 1
Delete, cost 1
Replace, cost 2
Edit distance: minimum number of edit operations
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distance("intention", "execution") = 8