In evolutionary robotics there has been research about the pursuit problem with different numbers of predators and prey: (i) one predator and one prey, (ii) many predators against one prey, and (iii) many predators against many prey. However, these different experiments are only involving food chains with two populations (two trophic levels). This dissertation uses three trophic levels to investigate if individuals in the middle trophic level perform equally or better than those that are been evolved in a two trophic level environment.
The investigation was done in a simulator called YAKS. A statistical analysis was conducted to evalutate the results. The result indicated that a robot with two tasks gets better at hunting and evading than robots with one task (either hunt or evade). Robots from the middle trophic level that are moving in the same direction as the camera is facing, were the best predators and prey. This dissertation is a step towards more complex and animal-like behaviours of robots.