Artificial intelligence and robotics
Artificial Intelligence - Lecture notes in computer science 178
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
The emergence of linguistic structure: an overview of the iterated learning model
Simulating the evolution of language
Guest Editors' Introduction: Semisentient Robots-- Routes to Integrated Intelligence
IEEE Intelligent Systems
Language Games for Autonomous Robots
IEEE Intelligent Systems
Open-ended category learning for language acquisition
Connection Science - Language and Robots
Cognitive Systems Research
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For robots to interact with humans at the language level, it becomes fundamental that robots and humans share a common language. In this paper, a social language grounding paradigm is adopted to teach a robotic arm basic vocabulary about objects in its environment. A human user, acting as an instructor, teaches the names of the objects present in their shared field of view. The robotic agent grounds these words by associating them to visual category descriptions. A component-based object representation is presented. An instance based approach is used for category representation. An instance is described by its components and geometric relations between them. Each component is a color blob or an aggregation of neighboring color blobs. The categorization strategy is based on graph matching. The learning/grounding capacity of the robot is assessed over a series of semi-automated experiments and the results are reported.