Effect of Different Breeding strategies on an Evolutionary learning algorithm

In this paper we seek to investigate the effects of different breeding strategies on the performance of an evolutionary algorithm. The strategies we explore can be split into two different categories, those that effect when an agent reproduces and those that decide which two agents are selected to reproduce. The different strategies that define when an agent reproduces are well explored and defined in evolutionary biology whereas the strategies we use for partner selection are less based on natural systems. This means that our areas of investigation will be see what partner selection strategy is most beneficial for each “when” strategy. To measure the performance of the system, each agent has a “fitness” which increases whenever they collect a piece of food, of which a fixed number are placed in the environment. We define the performance of a system as the average fitness of all agents in
the world.

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