Abstract
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
behavioural 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. 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
- acquisition,
- agents,
- algorithms,
- autonomous
- bases,
- bayesian
- behavioural
- belief
- conversational
- development,
- dialogue-act
- finite
- finite-state
- genetic
- intelligent
- knowledge
- language
- machines,
- matching
- matching,
- mental
- networks,
- pattern
- patterns,
- programming,
- software
- state
- templates,
Users
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