Lexicon Acquisition based on Behavior Learning

Studies on lexicon acquisition systems are gaining attention in hope for a natural human-robot interface and a test environment for theories of infant lexicon acquisition. This paper presents a system that forms word categories based on object-oriented behaviors. By using physical experiences, the system is able to generalize names to objects with various visual features. The system was implemented to a mobile robot acquiring lexicon about object categories with different rolling preferences. The system successfully acquired the lexicon and generalized the names to objects with various visual features in accordance with their rolling preferences