Evolving the "feeling" of time through sensory-motor coordination: A robot based model

In this paper, we aim to design decision-making mechanisms for an autonomous robot equipped with simple sensors, which integrates over time its perceptual experience in order to initiate a simple signalling response. Contrary to other similar studies, in this work the decision-making is uniquely controlled by the time-dependent structures of the agent's controller, which in turn are tightly linked to the mechanisms for sensory-motor coordination. The results of this work show that a single dynamic neural network, shaped by evolution, makes an autonomous agent capable of "feeling" time through the flow of sensations determined by its actions.