AutoMoDe-pomodoro
Nicolas Cambier, Eliseo Ferrante · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2022
In this paper, we reintroduce evolutionary algorithms into Auto-MoDe, an automatic design approach which optimizes behavioural modules into a probabilistic finite automaton. We evaluate three approaches, with different encodings of the probabilistic finite automaton phenotype, and observe their performances. This work opens modular designs to more advanced evolutionary robotics methods, such as novelty search and embodied evolution.