Grounding As Learning

Communication among agents requires (among many other things) that each agent be able to identify the semantic values of the generators of the language. This is the ”grounding” problem: how do agents with different cognitive and perceptual experiences successfully converge on common (or at least sufficiently similar) meanings for the language? There are many linguistic studies of how human learners do this, and also studies of how this could be achieved in robotic contexts (e.g., (Steels, 1996; Kirby, 1999)). These studies provide insight, but few of them characterize the problem precisely. In what range of environments can which range of languages be properly grounded by distributed agents? This paper takes a first step toward bringing the tools of formal language theory to bear on this problem. In the first place, these tools easily reveal a number of grounding problems which are simply unsolvable with reasonable assumptions about the evidence available, and some problems that can be solved. In the second place, these tools provide a framework for exploring more sophisticated grounding strategies (Stabler et al., 2003). We explore here some preliminary ideas about how hypotheses about syntactic structure can interact with hypotheses about grounding in a fruitful way to provide a new perspective on the emergence of recursion in language. Simpler grounding methods look for some kind of correlation between the mere occurrence of particular basic generators and semantic elements, but richer hypotheses about relations among the generators themselves can provide valuable additional constraints on the problem.