The spatial semantic hierarchy
Artificial Intelligence
Extended Homeostatic Adaptation: Improving the Link between Internal and Behavioural Stability
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Embodied spatial cognition: Biological and artificial systems
Image and Vision Computing
Memory-enhanced evolutionary robotics: the echo state network approach
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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To survive in an unknown environment an animal has to learn how to reach specific goal states. The animal is firstly guided by its reactive behavior motivated by its internal needs. After exploring the environment, contextual information can be used to optimally fulfill these internal needs. However, how a reactive and a contextual control system complement each other is still a fundamental question. Here, we address this problem from the perspective of the Distributed Adaptive Control architecture (DAC). We extend DAC's reactive layer with an allostatic control system and integrate it with its contextual control layer. Through robot foraging tasks we test the properties of the allostatic and contextual cozntrol systems and their interaction. We assess how they scale with task complexity. In particular, we show that the behavior generated by the contextual control layer is of particular importance when the system is facing conflict situations.