Reasoning from Incomplete Knowledge in a Procedural Deduction System
One very useful idea in AI research has been the notion of an explicit model of a problem situation. Procedural deduction languages, such as PLANNER, have been valuable tools for building these models. But PLANNER and its relatives are very limited in their ability to describe situations which are o...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/6898 |
| _version_ | 1826195131242381312 |
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| author | Moore, Robert Carter |
| author_facet | Moore, Robert Carter |
| author_sort | Moore, Robert Carter |
| collection | MIT |
| description | One very useful idea in AI research has been the notion of an explicit model of a problem situation. Procedural deduction languages, such as PLANNER, have been valuable tools for building these models. But PLANNER and its relatives are very limited in their ability to describe situations which are only partially specified. This thesis explores methods of increasing the ability of procedural deduction systems to deal with incomplete knowledge. The thesis examines in detail, problems involving negation, implication, disjunction, quantification, and equality. Control structure issues and the problem of modelling change under incomplete knowledge are also considered. Extensive comparisons are also made with systems for mechanica theorem proving. |
| first_indexed | 2024-09-23T10:07:50Z |
| id | mit-1721.1/6898 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:07:50Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/68982019-04-10T14:25:30Z Reasoning from Incomplete Knowledge in a Procedural Deduction System Moore, Robert Carter One very useful idea in AI research has been the notion of an explicit model of a problem situation. Procedural deduction languages, such as PLANNER, have been valuable tools for building these models. But PLANNER and its relatives are very limited in their ability to describe situations which are only partially specified. This thesis explores methods of increasing the ability of procedural deduction systems to deal with incomplete knowledge. The thesis examines in detail, problems involving negation, implication, disjunction, quantification, and equality. Control structure issues and the problem of modelling change under incomplete knowledge are also considered. Extensive comparisons are also made with systems for mechanica theorem proving. 2004-10-20T20:05:41Z 2004-10-20T20:05:41Z 1975-12-01 AITR-347 http://hdl.handle.net/1721.1/6898 en_US AITR-347 10580006 bytes 8308773 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | Moore, Robert Carter Reasoning from Incomplete Knowledge in a Procedural Deduction System |
| title | Reasoning from Incomplete Knowledge in a Procedural Deduction System |
| title_full | Reasoning from Incomplete Knowledge in a Procedural Deduction System |
| title_fullStr | Reasoning from Incomplete Knowledge in a Procedural Deduction System |
| title_full_unstemmed | Reasoning from Incomplete Knowledge in a Procedural Deduction System |
| title_short | Reasoning from Incomplete Knowledge in a Procedural Deduction System |
| title_sort | reasoning from incomplete knowledge in a procedural deduction system |
| url | http://hdl.handle.net/1721.1/6898 |
| work_keys_str_mv | AT moorerobertcarter reasoningfromincompleteknowledgeinaproceduraldeductionsystem |