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dc.contributor.authorMirza, N.A.
dc.contributor.authorNehaniv, C.L.
dc.contributor.authorDautenhahn, K.
dc.contributor.authorTe Boekhorst, R.
dc.date.accessioned2008-11-05T11:54:52Z
dc.date.available2008-11-05T11:54:52Z
dc.date.issued2008
dc.identifier.citationMirza , N A , Nehaniv , C L , Dautenhahn , K & Te Boekhorst , R 2008 , Anticipating future experience using grounded sensorimotor informational relationships . in In: Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems . MIT Press , pp. 412-419 .
dc.identifier.isbn978-0-262-75017-2
dc.identifier.otherPURE: 101268
dc.identifier.otherPURE UUID: 66ec17c7-3a97-487c-b07b-d45fd5fdddb1
dc.identifier.otherdspace: 2299/2553
dc.identifier.otherScopus: 84874631140
dc.identifier.urihttp://hdl.handle.net/2299/2553
dc.descriptionOriginal paper can be found at: http://www.alifexi.org/proceedings/#papers
dc.description.abstractOperational definitions and applications of the sensorimotor experience of an artificial embodied organism are presented along with a mathematical metric for distance between experiences based on Shannon information. We describe a simple robotic experiment that illustrates how an artificial embodied agent can use its own history of experience combined with the experience metric to predict future experience. Present sensorimotor experience is used to find the most similar past experience using the geometry of its growing and changing experience metric space. This is then used to ground the ontogeny of autonomous prospective capability in interacting with the environment, e.g. to anticipate forthcoming changes in environment based on temporally extended past experiences.en
dc.language.isoeng
dc.publisherMIT Press
dc.relation.ispartofIn: Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems
dc.titleAnticipating future experience using grounded sensorimotor informational relationshipsen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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