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COOPERATIVE KNOWLEDGE BASED PERCEPTUAL ANCHORING

Marios Daoutis, Silvia Coradeschi, Amy Loutfi

Year
2012
Citations
22

Abstract

In settings where heterogenous robotic systems interact with humans, information from the environment must be systematically captured, organized and maintained in time. In this work, we propose a model for connecting perceptual information to semantic information in a multi-agent setting. In particular, we present semantic cooperative perceptual anchoring, that captures collectively acquired perceptual information and connects it to semantically expressed commonsense knowledge. We describe how we implemented the proposed model in a smart environment, using different modern perceptual and knowledge representation techniques. We present the results of the system and investigate different scenarios in which we use the commonsense together with perceptual knowledge, for communication, reasoning and exchange of information.

Keywords

Computer sciencePerceptionCommonsense knowledgeCommonsense reasoningRepresentation (politics)Human–computer interactionArtificial intelligenceKnowledge representation and reasoningNatural language processing

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