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. Results are compared to a set of five fixed locomotion strategies and show that adaptive control can evolve and simultaneously optimise energy requirements, starting from the same locomotion non-adaptive strategies.
Idiotypic networks for evolutionary controllers in virtual creatures / Capodieci, Nicola; E., Hart; Cabri, Giacomo. - ELETTRONICO. - (2014), pp. 192-199. (Intervento presentato al convegno 14th International Conference on the Synthesis and Simulation of Living Systems (ALIFE 2014) tenutosi a New York, USA nel 30/7 - 2/8/2014) [10.7551/978-0-262-32621-6-ch032].