Show simple item record

dc.contributor.authorAkman, V.en_US
dc.contributor.authorten Hagen, P. J. W.en_US
dc.date.accessioned2016-02-08T10:56:50Z
dc.date.available2016-02-08T10:56:50Z
dc.date.issued1989en_US
dc.identifier.issn0738-4602
dc.identifier.urihttp://hdl.handle.net/11693/26234
dc.description.abstractCommonsense reasoning about the physical world, as exemplified by 'Iron sinks in water' or 'If a ball is dropped it gains speed,' will be indispensable in future programs. We argue that to make such predictions (namely, envisioning), programs should use abstract entities (such as the gravitational field), principles (such as the principle of superposition), and laws (such as the conservation of energy) of physics for representation and reasoning. These arguments are in accord with a recent study in physics instruction where expert problem solving is related to the construction of physical representations that contain fictitious, imagined entities such as forces and momenta. We give several examples showing the power of physical representations.en_US
dc.language.isoEnglishen_US
dc.source.titleAI Magazineen_US
dc.subjectPhysicsen_US
dc.subjectExpert problem Ssolvingen_US
dc.subjectPhysical representationsen_US
dc.subjectReasoningen_US
dc.subjectArtificial intelligenceen_US
dc.titleThe power of physical representationsen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage49en_US
dc.citation.epage65en_US
dc.citation.volumeNumber10en_US
dc.citation.issueNumber3en_US
dc.publisherAAAI Pressen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record