Attaining human–competitive game playing with genetic programming

Authors:
M. Sipper
Affiliations:
Department of Computer Science, Ben–Gurion University, Be'er Sheva, Israel
Venue:
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Year:
2006

Citing 0
Cited 4

Evolving strategy for a probabilistic game of imperfect information using genetic programming

Genetic Programming and Evolvable Machines
Dynamic population variation in genetic programming

Information Sciences: an International Journal
Evolving Teams of Cooperating Agents for Real-Time Strategy Game

EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Winning ant wars: evolving a human-competitive game strategy using fitnessless selection

EuroGP'08 Proceedings of the 11th European conference on Genetic programming

Quantified Score

Hi-index	0.00

Visualization

Abstract

We have recently shown that genetically programming game players, after having imbued the evolutionary process with human intelligence, produces human-competitive strategies for three games: backgammon, chess endgames, and robocode (tank-fight simulation) Evolved game players are able to hold their own – and often win – against human or human-based competitors This talk has a twofold objective: first, to review our recent results of applying genetic programming in the domain of games; second, to formulate the merits of genetic programming in acting as a tool for developing strategies in general, and to discuss the possible design of a strategizing machine.