The complementary roles of allostatic and contextual control systems in foraging tasks

Abstract

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 control 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. © 2010 Springer-Verlag.