The meaning of words in everyday language depends on two very different kinds of relations. On one hand, words refer to (are about) the world. This relation rests on causal interactions between information and the physical world. On the other hand, agents use words to pursue goals by producing speech acts. A complete model of language must bridge these two kinds of meaning.

These observations have motivated the implementation of a series of situated language processing systems in my lab. I will report on my ongoing attempt to develop a computational framework for language grounding that distills lessons learned from these implementations. Drawing from ideas in semiotics and constructivism, knowledge is represented in terms of signs which are causally connected to their referents, and actions which the agent can perform to verify, acquire, and use knowledge.

This framework may be useful for guiding the development of larger scale situated language processing systems, and to shed light on human cognitive processes.