Idiotypic networks for evolutionary controllers in virtual creatures
Cabri, G. (2014). Idiotypic networks for evolutionary controllers in virtual creatures. In: (Ed.) Proceedings of ALife, Fourteenth International Conference on the Synthesis and Simulation of Living Systems, , () ( ed.). (pp. ). : . MIT Press.
We propose a novel method for evolving adaptive locomotive strategies for virtual limbless creatures that addresses both functional and non-functional requirements, respectively the ability to avoid obstacles and to minimise spent energy. We describe an approach inspired by artificial immune systems, based on a dual-layer idiotypic network that results in a completely decentralised controller. Starting from a system initialised with five non-adaptive locomotion strategies, we show that an adaptive controller can evolve that both min- imises energy requirements and maximises distance covered when compared to the initial strategies.
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The Bio-Inspired Algorithms group within the Centre for Algorithms, Visualisation and Evolving Systems is a large and thriving group with interests in nature-inspired computing that include Evolutionary Computing, Hyper-Heuristics, Artificial Immune Systems and Swarm Intelligence.