A note on general adaptation in populations of painting robots

A population of virtual robots is evolved to perform the task of competitively painting the floor of a toroidal room. Two robots are present in any given room and paint using distinct colors. The fitness of a robot is the amount of floor painted with its own color, a situation where maximal marginal fitness comes from painting over squares already painted in an opponent’s color. The time required for a population to settle to a value close to its final average fitness is estimated experimentally at approximately 50 generations. Evolution is then continued well past this estimated settle-down point. The best robots in a given generation are saved at 500 and 5000 generations. The performance of highly evolved and less highly evolved robots is compared by placing the two types of robots into competition. The more evolved robots outperform the less evolved agents, with the empirical estimates of mean fitness differing by more than seven standard deviations. This occurs in spite ...

• Type: Conference
• Year: 2003
• Where: CEC
• Authors: Dan Ashlock, Elizabeth Blankenship, Jonathan Gandrud
• Keywords: Artificial Intelligence, CEC 2003, Evolved Robots, General Adaptation, Robots