Language Learning for the Autonomous Mental Development of Conversational Agents | Zendy

Jin-Hyuk Hong | Zendy; Sung-Soo Lim | Zendy; SungBae Cho | Zendy

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Language Learning for the Autonomous Mental Development of Conversational Agents

Author(s) -

Jin-Hyuk Hong,

Sung-Soo Lim,

SungBae Cho

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-46484-0

DOI - 10.1007/11893295_98

Subject(s) - computer science , human–computer interaction , artificial intelligence , intelligent agent , usability , mental state , reinforcement learning , development (topology) , programming language , cognitive science , psychology , mathematical analysis , mathematics

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.

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