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Gleap: A generalized program for game learning simulation 1
Author(s) -
Guthery Scott B.
Publication year - 1968
Publication title -
behavioral science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 45
eISSN - 1099-1743
pISSN - 0005-7940
DOI - 10.1002/bs.3830130411
Subject(s) - stochastic game , repeated game , computer science , set (abstract data type) , screening game , normal form game , class (philosophy) , mathematical economics , sequential game , combinatorial game theory , selection (genetic algorithm) , simultaneous game , non cooperative game , extensive form game , artificial intelligence , game theory , mathematics , programming language
GLEAP (Game LEArning Players) is an algorithmic structure within which a certain class of game situations and game player types may be defined and studied. When a GLEAP game and a set of GLEAP players have been defined, the GLEAP algorithm generates a sequential series of plays of the game by the set of players. The fundamental operating assumption made about GLEAP players is that they base alternative selection decisions solely upon their past payoff experience with each alternative available.