The interaction of brain, body and environment can result in complex behavior with rich dynamics even for relatively simple agents. Such dynamics are, however, often notoriously difficult to analyze. In this paper we explore the case of a simple simulated robotic agent, equipped with a reactive neurocontroller and an energy level, that the agent has been evolved to re-charge. A dynamical systems analysis, shows that a non-neural internal state (energy level), despite its simplicity, dynamically

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... modulates the agent-environment system's behavioral attractors, such that the robot's behavioral repertoire is continually adapted to its current situation and energy level.