Evolving cooperative strategies for UAV teams

We present a Genetic Programming approach to evolve cooperative controllers for teams of UAVs. Our focus is a collaborative search mission in an uncertain and/or hostile environment. The controllers are decision trees constructed from a set of low-level functions. Evolved decision trees are robust to changes in initial mission parameters and approach the optimal bound for time-to-completion. We compare results between steady-state and generational approaches, and examine the effects of two common selection operators. Categories and Subject Descriptors I.2.2 [Automatic Programming]: [Program Synthesis]; I.2.11 [Distributed Artificial Intelligence]: [Multiagent Systems] General Terms Experimentation, Performance Keywords Autonomous control, cooperative agents, genetic programming, simulated robotics

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Marc D. Richards, L. Darrell Whitley, J. Ross Beveridge, Todd Mytkowicz, Duong Nguyen, David Rome
• Keywords: Decision Trees, GECCO 2005, Genetic Programming, Genetic Programming Approach