Using Genetic Programming with Multiple Data Types and Automatic Modularization to Evolve Decentralized and Coordinated Navigation in Multi-Agent Systems
نویسندگان
چکیده
This work applies PushGP (a multi-type, automatically modularizing genetic programming system) to the 3D Opera problem (a cooperation and navigation multi-agent task involving the movement of a 3D swarm of agents through a constrained exit point). Within this framework we explore the effect of adding task-specific data types to the GP system. In particular, we extend the native types of PushGP to include 3D vectors, and we compare the results with and without this extension to each other and to human-programmed agent controllers.
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