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A Framework for Representing Knowledge

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dc.contributor.author Minsky, Marvin en_US
dc.date.accessioned 2004-10-04T14:38:58Z
dc.date.available 2004-10-04T14:38:58Z
dc.date.issued 1974-06-01 en_US
dc.identifier.other AIM-306 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/6089
dc.description.abstract This is a partial theory of thinking, combining a number of classical and modern concepts from psychology, linguistics, and AI. Whenever one encounters a new situation (or makes a substantial change in one's viewpoint) he selects from memory a structure called a frame, a remembered framework to be adopted to fit reality by changing details as necessary. A frame is a data-structure for representing a stereotyped situation, like being in a certain kind of living room, or going to a child's birthday party. Attached to each frame are several kinds of information. Some of this information is about how to use the frame. Some is about what one can expect to happen next. Some is about what to do if these expectations are not confirmed. The "top levels" of a frame are fixed, and represent things that are always true about the supposed situation. The lower levels have many "alota" that must be filled by specific instances or data. Collections of related frames are linked together into frame-systems. The effects of important actions are mirrored by transformations between the frames of a system. These are used to make certain kinds of calculations economical, to represent changes of emphasis and attention and to account for effectiveness of "imagery". In Vision, the different frames of a system describe the scene from different viewpoints, and the transformations between one frame and another represent the effects of moving from place to place. Other kinds of frame-systems can represent actions, cause-effect relations, or changes in conceptual viewpoint. The paper applies the frame-system idea also to problems of linguistic understanding: memory, acquisition and retrieval of knowledge, and a variety of ways to reason by analogy and jump to conclusions based on partial similarity matching. en_US
dc.description.provenance Made available in DSpace on 2004-10-04T14:38:58Z (GMT). No. of bitstreams: 2 AIM-306.ps: 8243582 bytes, checksum: 87053cfed7124e8608a2907b6fe5a623 (MD5) AIM-306.pdf: 5793486 bytes, checksum: 0670b6b27f260f30fd8ba4d058dcf932 (MD5) Previous issue date: 1974-06-01 en
dc.format.extent 82 p. en_US
dc.format.extent 8243582 bytes
dc.format.extent 5793486 bytes
dc.format.mimetype application/postscript
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartofseries AIM-306 en_US
dc.title A Framework for Representing Knowledge en_US

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