| dc.creator | Borchardt, Gary C. | |
| dc.date | 2004-10-04T14:16:02Z | |
| dc.date | 2004-10-04T14:16:02Z | |
| dc.date | 1993-02-01 | |
| dc.date.accessioned | 2013-10-09T02:42:05Z | |
| dc.date.available | 2013-10-09T02:42:05Z | |
| dc.date.issued | 2013-10-09 | |
| dc.identifier | AIM-1403 | |
| dc.identifier | http://hdl.handle.net/1721.1/5955 | |
| dc.identifier.uri | http://koha.mediu.edu.my:8181/xmlui/handle/1721 | |
| dc.description | Causal reconstruction is the task of reading a written causal description of a physical behavior, forming an internal model of the described activity, and demonstrating comprehension through question answering. T his task is difficult because written d escriptions often do not specify exactly how r eferenced events fit together. This article (1) ch aracterizes the causal reconstruction problem, (2) presents a representation called transition space, which portrays events in terms of "transitions,'' or collections of changes expressible in everyday language, and (3) describes a program called PATHFINDER, which uses the transition space representation to perform causal reconstruction on simplified English descriptions of physical activity. | |
| dc.format | 61 p. | |
| dc.format | 548466 bytes | |
| dc.format | 2780985 bytes | |
| dc.format | application/octet-stream | |
| dc.format | application/pdf | |
| dc.language | en_US | |
| dc.relation | AIM-1403 | |
| dc.subject | knowledge representation | |
| dc.subject | explanation | |
| dc.subject | causal reasoning | |
| dc.subject | sanalogy | |
| dc.subject | abstraction | |
| dc.subject | natural language | |
| dc.title | Causal Reconstruction |
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