| Abstract: |
This paper proposes a computational model for children's word
acquisition based on inductive logic programming. There are three fundamental
features in our approach. Firstly, we incorporate cognitive biases developed
recently to explain the efficiency of children's language acquisition. Secondly,
we design a co-evolution mechanism of acquiring concept definitions for
words and developing concept hierarchy. Concept hierarchy plays an important
role of defining contexts for later word learning processes. A context switching
mechanism is used to select a relevant set of attributes for learning a
word depending on the category which it belongs to. On the other hand, during
acquiring definitions for words, concept hierarchy is developed. Thirdly,
we pursue resemblance to human brain in functional level.
We developed an experimental language acquisition system called WISDOM
(Word Induction System for Deriving Object Model) and conducted virtual
experiments or simulations on acquisition of words in two different categories.
The experiments shows feasibility of our approach.
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