Emergent Instinctive Behaviour in Evolved Neuro-inspired Agents

Abstract. We investigate the emergence of intelligent behaviour of an agent in the classic AI learning environment known as Wumpus World. The agent is given a ’brain ’ that is a new type of developmental neuro-inspired computational network. The neurons are defined by a genotype consisting of seven computational functions that represent electrical and developmental processes inside neuron. The computational functions are evolved using a form of Genetic Programming known as Cartesian Ge-netic Programming. The ’brain ’ that occurs by running the genetic pro-grams has a highly dynamic morphology in which neurons grow, and die, and neurite branches together with synaptic connections form and change in response to situations encountered in the external environ-ment. We present results and analyse characteristics of the model and find that the agents exhibit ’instinctive ’ behaviour and develop memory