Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/22948
Title: Evolving opponents for interesting interactive computer games
Authors: Yannakakis, Georgios N.
Hallam, John
Keywords: Computer games
Human-computer interaction
Issue Date: 2004
Publisher: MIT PRESS
Citation: Yannakakis, G. N., & Hallam J. (2004). Evolving opponents for interesting interactive computer games. 8th International Conference on the Simulation of Adaptive Behavior (SAB’04); From Animals to Animats 8, Los Angeles. 499-508.
Abstract: In this paper we introduce experiments on neuro-evolution mechanisms applied to predator/prey multi-character computer games. Our test-bed is a modified version of the well-known Pac-Man game. By viewing the game from the predators’ (i.e. opponents’) perspective, we attempt off-line to evolve neural-controlled opponents capable of playing effectively against computer-guided fixed strategy players. However, emergent near-optimal behaviors make the game less interesting to play. We therefore discuss the criteria that make a game interesting and, furthermore, we introduce a generic measure of predator/prey computer games’ interest. Given this measure, we present an evolutionary mechanism for opponents that keep learning from a player while playing against it (i.e. on-line) and we demonstrate its efficiency and robustness in increasing and maintaining the game’s interest. Computer game opponents following this on-line learning approach show high adaptability to changing player strategies which provides evidence for the approach’s effectiveness against human players.
URI: https://www.um.edu.mt/library/oar//handle/123456789/22948
Appears in Collections:Scholarly Works - InsDG

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