Multi-agent reinforcement learning and chimpanzee hunting

The use of multi-agent reinforcement learning is growing because of it´s ability to scale in complexity and its lack of need for knowledge of the state and other agents. Chimpanzee hunting behavior is a suitable complex and interesting model for which multi-agent reinforcement learning is appropriate. Chimpanzee hunting strategies vary in both use and complexity and ultimately depend on the environment for which they are applied. Learning to use the varying strategies and learning when they are most effective is what this paper addresses and provides initial results and framework to build upon.