異種群ロボットの進化における特化した集団行動の創発
Emergence of specialized Collective Behaviors in Evolving Heterogeneous Swarms
表現型可塑性を持つシミュレーションロボット群を進化させ、サブグループ間の相互作用から特化した集団行動が創発することを示し、オンライン調節機構で性能と拡張性を向上させた。
著者: Fuda van Diggelen, Matteo De Carlo, Nicolas Cambier, Eliseo Ferrante, A. E. Eiben
分類: cs.RO, cs.AI
原文アブストラクト
Natural groups of animals, such as swarms of social insects, exhibit astonishing degrees of task specialization, useful to address complex tasks and to survive. This is supported by phenotypic plasticity: individuals sharing the same genotype that is expressed differently for different classes of individuals, each specializing in one task. In this work, we evolve a swarm of simulated robots with phenotypic plasticity to study the emergence of specialized collective behavior during an emergent perception task. Phenotypic plasticity is realized in the form of heterogeneity of behavior by dividing the genotype into two components, with one different neural network controller associated to each component. The whole genotype, expressing the behavior of the whole group through the two components, is subject to evolution with a single fitness function. We analyse the obtained behaviors and use the insights provided by these results to design an online regulatory mechanism. Our experiments show three main findings: 1) The sub-groups evolve distinct emergent behaviors. 2) The effectiveness of the whole swarm depends on the interaction between the two sub-groups, leading to a more robust performance than with singular sub-group behavior. 3) The online regulatory mechanism enhances overall performance and scalability.
