Learning benefits evolution if sex gives pleasure

Abstract-- In this paper we investigate the effects of individual learning on an evolving population of situated agents. We work with a novel type of system where agents can decide autonomously (by their controllers) if/when they reproduce and the bias in the agent controllers for the mating action is adaptable. Our experiments show that in such a system reinforcement learning with the straightforward rewards system based on energy makes the agents loose their interest in mating, that is, learning counteracts evolution. This effect can be eliminated by introducing a specific reward for the mating action that always gives positive feedback to the agents, as some kind of pleasure or "orgasm". Using such a combination, individual learning is able to keep non-optimal agents alive, where evolution only leads to extinction. Despite that it preserves a viable population that is able to acquire the necessary survival skills, we also found a disadvantage of learning, namely a hiding e...

• Type: Conference
• Year: 2008
• Where: CEC
• Authors: Robert Griffioen, Selmar K. Smit, A. E. Eiben
• Keywords: Agent Controllers, Artificial Intelligence, CEC 2008, Individual Learning, Reinforcement Learning