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- W2123238280 abstract "<para xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> In recent years, the concept of “autonomous mental development” (AMD) has been applied to the construction of artificial systems such as conversational agents, in order to resolve some of the difficulties involved in the manual definition of their knowledge bases and behavioral patterns. AMD 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 (GP). Knowledge acquisition implemented by finite-state machines and templates, and language learning by GP are used for language development. Several illustrations and usability tests show the usefulness of the proposed developmental conversational agent. </para>" @default.
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- W2123238280 date "2007-04-01" @default.
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- W2123238280 title "Autonomous Language Development Using Dialogue-Act Templates and Genetic Programming" @default.
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- W2123238280 doi "https://doi.org/10.1109/tevc.2006.890265" @default.
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