Evolution for modeling: a genetic programming framework for sesam
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
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An agent system that develops and evolves its own structure can facilitate more accurate responses to complex environments. The purpose of the paper then is to explore this idea built upon our unmanned aerial vehicle (UAV) swarm model and simulation that uses autonomous self-organized concepts. The specific objective is to re-engineer this UAV foundation based upon a formal design model with focus on bio-inspired agent attack through emergent control structures. The overall design approach should give UAVs or generic agents the ability to not only react to dynamic environments but develop the controls in order to change behaviors spontaneously. To allow these behaviors to properly evolve, a multi-objective evolutionary algorithm generates a self-organized rule-based agent swarm. Heterogeneous UAV swarms are tested against difficult targeting scenarios that evolve specific attack behaviorial techniques. Statistical observations indicate that bio-inspired techniques integrated with the emerging entangled (non-hierarchical) framework provide desired complex UAV swarming behaviors in dynamic environments.