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
Intelligence without representation
Artificial Intelligence
Language Games for Autonomous Robots
IEEE Intelligent Systems
Evolution of communication and language using signals, symbols, andwords
IEEE Transactions on Evolutionary Computation
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We describe a novel approach to anchoring symbols in the sensory data of a hybrid autonomous system. Using an autonomous mobile robot as a test platform we show how an Isomap can be used to detect and properly classify time-series of sensory data. In the past, similar approaches have used self-organizing maps (SOMs) for this purpose. Isomap can be regarded as an improved technique for generating a topology preserving low-dimensional embedding of higher-dimensional data. The interactions of the robot with objects in its environment produce a sequence of points on the map. For object recognition, these sequences need to be correctly classified. This technique forms the basis of our symbol anchoring architecture.