Extending the temporal horizon of autonomous robots

We introduce mathematically rigorous metrics on agent experiences having various temporal horizons. Sensorimotor variables accessible to the agent are--treated as information-theoretic sources modelled as random variables. The time series from the sensorimotor variables over a given temporal region for different behavioural contexts ground an agent-based view of the agent's own experiences, and the information-theoretic differences between sensorimotor experiences induce a metric space structure on the set of the agent's possible experiences. This could allow an autonomous mobile robot to locate and navigate between its sensorimotor--experiences on a geometric landscape (an experiential metric space) whose points are its possible experiences of a given temporal scope and in which nearby points are similar experiences.