<p>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.</p><p>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.</p>

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.

We investigate an approach to apply Genetic Programming for the evolution of optimal escaping strategies of a team of caribou agents in the wolf-caribou predator prey problem (WCPPP) where the WCPPP is comprised of a team of caribou agents attempting to escape from a single yet superior (in terms of sensory abilities, raw speed, and maximum energy) wolf agent in a simulated twodimensional infinite toroidal world. We empirically verify our hypothesis that the incorporation of empathy in caribou agents significantly improves both the evolution efficiency of the escaping behavior and the effectiveness of such a behavior. This finding may be viewed as a verification of the survival value of empathy and the resulting compassionate behavior of the escaping caribou agents. Moreover, considering the fact that a single caribou cannot escape from the superior wolf, the ability of a team of empathic caribou agents to escape may also be viewed as an illustration of the emergent nature of a successful escaping behavior – in that the team-level properties are more than the mere sum of the properties of the individual entities. Within this context, we also present empirical results that verify the complex (nonlinear) nature of the relationship between the size of team of caribou agents and the efficiency of their escaping behavior. / 博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University