Spatial inconsistency of memorized positions produces different types of movements

Animals are known to use information such as spatial memory in order to search for or relocate their goals. Some animals show self-avoiding walks to present straight movements. Interesting, animals alter their migratory and diffusive behaviors in response to their own experiences or independently in a similar environment. To tackle this problem by focusing on the decision-making of the random walker, we developed an artificial agent-based model in which the agent considers the time series of its memorized locations. In our proposed model, the agent sometimes regards part of its memorized cells as past information and changes its directional rule in order to not to revisit those locations. Experimental results demonstrated that the agent succeeded in producing both super-diffusive walks and sub-diffusive walks. Importantly, these various characteristic movements emerge without any adjustments of parameters.