Emergent action language on real robots

Abstract

Almost all languages in the world have a way to formulate commands. Commands specify actions that the body should undertake (such as “stand up”), possibly involving other objects in the scene (such as “pick up the red block”). Action language involves various competences, in particular (i) the ability to perform an action and recognize which action has been performed by others (the so-called mirror problem), and (ii) the ability to identify which objects are to participate in the action (e.g. “the red block” in “pick up the red block”) and understand what role objects play, for example whether it is the agent or undergoer of the action, or the patient or target (as in “put the red block on top of the green one”). This chapter describes evolutionary language game experiments exploring how these competences originate, can be carried out and acquired, by real robots, using evolutionary language games and a whole systems approach.