Survey of Evolutionary Behavior Tree Algorithm

doi:10.16182/j.issn1004731x.joss.21-FZ0753

Abstract

Abstract: Evolutionary behavior tree method is an agent behavior modeling method which uses evolutionary algorithm to generate and optimize behavior tree model. Based on the background knowledge of behavior tree and evolutionary algorithm, three kinds of evolutionary behavior tree algorithms based on genetic programming, grammar evolution and hybrid algorithm as well as corresponding improved algorithms are described, and the advantages and disadvantages of different algorithms are analyzed and compared. The specific applications of evolutionary behavior tree in combat simulation, game artificial intelligence, robotics and other fields are summarized. The future development trends of evolutionary behavior tree are proposed and discussed from the perspectives of search ability, generalization ability, behavior tree optimization and multi-agent application.

Key words: evolutionary behavior tree, behavior tree, genetic programming, grammar evolution, hybrid algorithm

CLC Number:

TP391.9

Yang Jie, Zhang Qi, Zeng Junjie, Yin Quanjun. Survey of Evolutionary Behavior Tree Algorithm[J]. Journal of System Simulation, 2021, 33(10): 2315-2322.

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