Epigenetic Operators and the Evolution of Physically Embodied Robots

Jake Brawer, Aaron Hill, Ken Livingston, Eric Aaron, Joshua Bongard, John H. Long
2017 Frontiers in Robotics and AI  
The genetic operators (GOs) of recombination, mutation, and selection are commonly included in studies of evolution and evolvability, but they are not the only operators that can affect the genotype-to-phenotype (G → P) map and thus the outcomes of evolution. In this paper, we present experiments with an epigenetic operator (EO), interactive wiring of a circuit, alongside common GOs, investigating both epigenetic and GO effects on the evolution of both simulated and physically embodied
more » ... rg-inspired robots. As a platform for our experiments, we built a system that encoded the genetics for the physical circuitry of the analog robots and made explicit rules for how that circuitry would be constructed; phenotypic expression consisted of the placement of wires to form the circuitry and thus govern robot behavior. We then varied the presence of gene interactions across populations of robots, studying how the EO-and its effects on G → P maps-affected the results of evolution over several generations. Additionally, a variant of these experiments was run in simulation to provide an independent test of the evolutionary impact of this EO. Our results demonstrate that robot populations with the EO had quantitatively different and potentially less adaptive evolution than populations without it. For example, selection increased the rate at which functional circuitry was lost in the population with the EO, compared to the population without it. In addition, in simulation, EO populations were significantly less fit than populations without it. More generally, results such as these demonstrate the interaction of genetic and EOs during evolution, suggesting the broad importance of including EOs in investigations of evolvability. To our knowledge, our work represents the first physically embodied EO to be used in the evolution of physically embodied robots.
doi:10.3389/frobt.2017.00001 fatcat:276oeehcbbahhd3b2tr3npxhgu