Evolutionary Induction of Grammar Systems for Multi-agent Cooperation

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Abstract

We propose and describe a minimal cooperative problem that captures essential features of cooperative behavior and permits detailed study of the mechanisms involved. We characterize this problem as one of language generation by cooperating grammars, and present initial results for language induction by pairs of right-linear grammars using grammatically based genetic programming. Populations of cooperating grammar systems were found to induce grammars for regular languages more rapidly than non-cooperating controls. Cooperation also resulted in greater absolute accuracy in the steady state, even though the control performance exceeded that of prior results for the induction of regular languages by a genetic algorithm. © Springer-Verlag 2004.

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Johnson, C. M., & Farrell, J. (2004). Evolutionary Induction of Grammar Systems for Multi-agent Cooperation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3003, 101–112. https://doi.org/10.1007/978-3-540-24650-3_10

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