Embodied anticipation in neurocomputational cognitive architectures for robotic agents

The coupling between a body (in an extended sense that encompasses both neural and non-neural dynamics) and its environment is here conceived as a critical substrate for cognition. We propose and discuss the plan for a neurocomputational cognitive architecture for robotic agents, so far implemented in its minimal form for supporting the behavior of a simple simulated robotic agent. A non-neural internal bodily mechanism (crucially characterized by a time scale much slower than the normal sensory-motor interactions of the robot with its environment) extends the cognitive potential of a system composed of purely reactive parts with a dynamic action selection mechanism and the capacity to integrate information over time. The same non-neural mechanism is the foundation for a novel, minimalist anticipatory architecture, implementing our bodily-anticipation hypothesis and capable of swift readaptation to related yet novel tasks.1