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17

AGENTS
2000
Springer

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Unsupervised clustering of robot activities: a Bayesian approach

13 years 8 months ago

Unsupervised clustering of robot activities: a Bayesian approach

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Our goal is for robots to learn conceptual systems su cient for natural language and planning. The learning should be autonomous, without supervision. The rst steps in building a conceptual system are to say some things are alike and others are di erent, based on how an agent interacts with them, and to organize similar things into classes or clusters. We use the bcd algorithm for clustering episodes experienced by our robots. The clusters contain episodes with similar dynamics, described by Markov chains.

Marco Ramoni, Paola Sebastiani, Paul R. Cohen

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Added	01 Aug 2010
Updated	01 Aug 2010
Type	Conference
Year	2000
Where	AGENTS
Authors	Marco Ramoni, Paola Sebastiani, Paul R. Cohen

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