Evolving Plastic Neuromodulated Networks for Behavior Emergence of Autonomous Virtual Characters

This paper addresses the problem of generating natural be-havior of autonomous virtual characters. Inspired by the fields of Embodied and Enactive Artificial Intelligence, we postulate that natural behavior is the result of a coupling be-tween the agent and the world where it lives, which leads to a coherence between its actions and its surroundings. In this work, we present the tools that we have been using to study that idea: a controller based on a plastic neuromodulated neu-ral network, which is capable of molding itself to received stimuli; and a simple novel method for genetic encoding of artificial neural networks. We show the capabilities of the controller in generating interesting foraging behavior of an autonomous virtual robot, and discuss the advantages of its emergent characteristics when compared with traditional ap-proaches