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Title: Robot survival strategies
Author: Askew, Andrew P.
ISNI:       0000 0004 2724 5155
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2010
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A fundamental question in biology is how cooperation and especially altruism evolves in nature. There is debate as to whether altruism evolves by individual or group selection and if kin selection is the key explanation. Recent research in evolutionary robotics has provided some evidence that altruism emerges in populations of evolving robot controllers. A set of experiments is presented here that evolve heterogeneous, but related, populations of simulated abstract robot controllers with a biologically inspired implicit fitness function based simply on 'eating' enough to survive. In predator-prey simulations, an internal fitness function that is implicit in the selection of individuals is implemented. Predators are paired in a series of trials where they interact to 'consume' the prey and those that survive are selected to reproduce and proceed to the next generation. When individual level selection is implemented, true artificial altruism emerges naturally, where an individual sacrifices its own 'life' so as to allow a related robot to survive. The altruistic trait evolves in situations where there is a high probability that neither of a pair would be successful if both attempt to survive. When situated communication is available, it is used by a robot to claim the prey once located, signalling to the other robot to behave altruistically. Under 'breeding pair' level selection where a pair of robots are required to survive together, they cooperate to ensure that both are successful and when situated communication is available, it is used by the robots to signal that the prey has been located, increasing the amount of collaboration in the population. In selecting for competition, where the robots are not allowed to survive as a pair, in addition to competing, the robots also act altruistically to achieve the goal of only one survivor.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available