Simulating exploration versus exploitation in agent foraging under different environment uncertainties.

For artificial agents trading off exploration (food seeking) versus (short-term) exploitation (or consumption), our experiments suggest that uncertainty (interpreted information, theoretically) magnifies food seeking. In more uncertain environments, with food distributed uniformly randomly, exploration appears to be beneficial. In contrast, in biassed (less uncertain) environments, with food concentrated in only one part, exploitation appears to be more advantageous. Agents also appear to do better in biassed environments.