Improving the adaptability of simulated evolutionary swarm robots in dynamically changing environments.

ABSTRACT: One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN). An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furth

SUBMITTER: Yao Y 

PROVIDER: S-EPMC3944896 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature