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'''Opponent Model Search''' incorporates asymmetric search and [[Asymmetric Evaluation|asymmetric evaluation]] techniques considering the peculiarities of an opponent, which requires explicit [[Knowledge|knowledge]] or assumption, and includes a model on how the opponent evaluates positions. Naive approaches in computer chess tournaments are [[Opening Book|opening book]] preparation and [[Contempt Factor|contempt]]. Some chess programs, notably [[Psion]] <ref>[[Kaare Danielsen]] ('''1987'''). ''The 7th World Microcomputer Chess Championship, Rome, Italy, September 14-20, 1987''. [[ICGA Journal#10_3|ICCA Journal, Vol. 10, No. 3]] » [[WMCCC 1987]]</ref> , its successor [[Chess Genius]] <ref>[http://groups.google.com/group/rec.games.chess.computer/browse_frm/thread/b456400a43207b02 Genius' asymmetric-search by example: TRY yourself] by [[Thorsten Czub]], [[Computer Chess Forums|rgcc]], December 30, 1997</ref> , and [[KnightCap]] <ref>[https://groups.google.com/group/rec.games.chess.computer/msg/f9bfe5d4457a19ad asymmetry] by [[Andrew Tridgell]], [[Computer Chess Forums|rgcc]], August 12, 1997</ref> , apply [[Asymmetric evaluation|asymmetric evaluation]] and search, for instance to [[Extensions|extend]] when the own side is in trouble but not the opponent. Other programs, like [[Crafty]], can be adapted asymmetric for playing human chess players, specially [[Anti-Computerchess|anti-computerchess]] specialists, for instance to reduce the program's tendency to trade material and to avoid blocked positions with a high [[Pawn Rams (Bitboards)|rammed pawn]] versus [[Pawn Levers (Bitboards)|lever]] ratio. [[Ed Schroder|Ed Schröder]] proposed to reward own [[Hanging Piece|hanging pieces]] to encourage complicated, [[Tactics|tactical]] play versus humans, and to keep opponents under time pressure in playing immediate [[Pondering|ponder hits]] <ref>[http://www.open-chess.org/viewtopic.php?f=5&t=2546&start=1 Re: Anti Coward Mode] by [[Ed Schroder|Rebel]], [[Computer Chess Forums|OpenChess Forum]], December 22, 2013</ref> . Programs may [[Automated Tuning|tune]] and [[Learning|learn]] feature vectors and their respective weights to maximize result scores against certain opponents as well.