Language learning for the autonomous mental development of conversational agents

Authors:
Jin-Hyuk Hong;Sungsoo Lim;Sung-Bae Cho
Affiliations:
Dept. of Computer Science, Yonsei University, Sinchon-dong, Sudaemoon-ku, Seoul, Korea;Dept. of Computer Science, Yonsei University, Sinchon-dong, Sudaemoon-ku, Seoul, Korea;Dept. of Computer Science, Yonsei University, Sinchon-dong, Sudaemoon-ku, Seoul, Korea
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

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Abstract

Since the manual construction of our knowledge-base has several crucial limitations when applied to intelligent systems, mental development has been investigated in recent years. Autonomous mental development is a new paradigm for developing autonomous machines, which are adaptive and flexible to the environment. Language development, a kind of mental development, is an important aspect of intelligent conversational agents. In this paper, we propose an intelligent conversational agent and its language development mechanism by putting together five promising techniques; Bayesian networks, pattern matching, finite state machines, templates, and genetic programming. Knowledge acquisition implemented by finite state machines and templates, and language learning by genetic programming are developed for language development. Several illustrations and usability tests show the usefulness of the proposed developmental conversational agent.