Title :
Playing the Rock-Paper-Scissors game with a genetic algorithm
Author :
Ali, F.F. ; Nakao, Z. ; Wei, Yen
Author_Institution :
Dept. of Manage. & Inf. Syst., Meio Univ., Okinawa, Japan
Abstract :
This paper describes a strategy to follow whilst playing the Rock-Paper-Scissors game. Instead of making a biased decision, a rule is adopted where the outcomes of the game from the last few turns are observed and then a deterministic decision is made. Such a strategy is encoded into a genetic string and a genetic algorithm works on a population of such strings. Good strings are produced in later generations. Such a strategy is found to be successful, and its efficiency is demonstrated by testing the strategy against both systematic and human strategies
Keywords :
game theory; genetic algorithms; cooperative short memory behavior; deterministic decision; evolutionary systems; game theory; genetic algorithm; genetic string; historical behavior; human strategies; opponent; outcomes; rock-paper-scissors game; Biological system modeling; Engineering management; Game theory; Genetic algorithms; Genetic engineering; History; Humans; Information management; Management information systems; System testing;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870372