Affiliation:
1. Comenius University-Bratislava, Slovakia
Abstract
In this chapter, we focus on the issue of understanding in various types of agents. Our main goal is to build up notions of meanings and understanding in neutral and non-anthropocentric terms that would not exclude preverbal living organisms and artificial systems by definition. By analyzing the evolutionary context of understanding in living organisms and the representation of meanings in several artificially built systems, we come to design principles for building “understanding” artificial agents and formulate necessary conditions for the presence of inherent meanings. Such meanings should be based on interactional couplings between the agents and their environment, and should help the agents to orient themselves in the environment and to satisfy their goals. We explore mechanisms of action-based meaning construction, horizontal coordination, and vertical transmission of meanings and exemplify them with computational models.
Reference76 articles.
1. Bergen, B., & Chang, N. (2003). Embodied construction grammar in simulation-based language understanding. In J. O. Ostman & M. Fried (Eds.), Construction grammar(s): Cognitive and cross-language dimensions (pp. 147-190). Amsterdam: Johns Benjamins.
2. Bloom, P. (2000). How children learn the meanings of words. Cambridge, MA: MIT Press.
3. Bodík, P., & Takáč, M. (2003). Formation of a common spatial lexicon and its change in a community of moving agents. In B. Tessem, P. Ala-Siuru, P. Doherty, & B. Mayoh (Eds.), Frontiers in AI: Proceedings of the Eighth Scandinavian Conference on Artificial Intelligence SCAI’03 (pp. 37-46). Amsterdam: IOS Press.
4. Briscoe, T. (Ed.). (2001). Linguistic evolution through language acquisition: Formal and computational models. Cambridge, U. K.: Cambridge University Press.
5. Intelligence without representation