Evolution of Artificial Intelligence in the Game of Tag
نویسندگان
چکیده
This paper describes evolution of artifical intelligent in the Game of Tag. In our simulator, artificial agents are classified as ’it’ (predator) and ’non-it’ (prey) and assigned symmetrical goals : pursuit and evasion respectively. Instead of using explicit fitness functions, predators and preys are evolved solely based on their pursuit and evasion records. Each agent has own artifical intelligent which is represented as a set of lisp-style predicates including sensor data, conditional statement and numerical operations. Even though we have two separate species, ’it’ and ’non-it’, we initialize and mutate their A.I. in the same method and probability distribution. The evolved ’it’ and ’non-it’ have their own style of strategies and show agile pursuit and evasion behaviors.
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