The Use of Parallelism to Implement a Heuristic Search
The role of parallel processing in heuristic search is examined by means of an example (cryptarithmetic addition). A problem solver is constructed that combines the metaphors of constraint propagation and hypothesize-and-test. The system is capable of working on many incompatible hypotheses at...
| Main Author: | |
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| Language: | en_US |
| Published: |
2004
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| Online Access: | http://hdl.handle.net/1721.1/6352 |
| _version_ | 1811082798509850624 |
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| author | Kornfeld, William A. |
| author_facet | Kornfeld, William A. |
| author_sort | Kornfeld, William A. |
| collection | MIT |
| description | The role of parallel processing in heuristic search is examined by means of an example (cryptarithmetic addition). A problem solver is constructed that combines the metaphors of constraint propagation and hypothesize-and-test. The system is capable of working on many incompatible hypotheses at one time. Furthermore, it is capable of allocating different amounts of processing power to running activities and and changing these allocations as computation proceeds. It is empirically found that the parallel algorithm is, on the average, more efficient than a corresponding sequential one. Implications of this for problem solving in general are discussed. |
| first_indexed | 2024-09-23T12:09:11Z |
| id | mit-1721.1/6352 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:09:11Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/63522019-04-10T18:32:46Z The Use of Parallelism to Implement a Heuristic Search Kornfeld, William A. The role of parallel processing in heuristic search is examined by means of an example (cryptarithmetic addition). A problem solver is constructed that combines the metaphors of constraint propagation and hypothesize-and-test. The system is capable of working on many incompatible hypotheses at one time. Furthermore, it is capable of allocating different amounts of processing power to running activities and and changing these allocations as computation proceeds. It is empirically found that the parallel algorithm is, on the average, more efficient than a corresponding sequential one. Implications of this for problem solving in general are discussed. 2004-10-04T14:52:48Z 2004-10-04T14:52:48Z 1981-03-01 AIM-627 http://hdl.handle.net/1721.1/6352 en_US AIM-627 5613932 bytes 3675451 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | Kornfeld, William A. The Use of Parallelism to Implement a Heuristic Search |
| title | The Use of Parallelism to Implement a Heuristic Search |
| title_full | The Use of Parallelism to Implement a Heuristic Search |
| title_fullStr | The Use of Parallelism to Implement a Heuristic Search |
| title_full_unstemmed | The Use of Parallelism to Implement a Heuristic Search |
| title_short | The Use of Parallelism to Implement a Heuristic Search |
| title_sort | use of parallelism to implement a heuristic search |
| url | http://hdl.handle.net/1721.1/6352 |
| work_keys_str_mv | AT kornfeldwilliama theuseofparallelismtoimplementaheuristicsearch AT kornfeldwilliama useofparallelismtoimplementaheuristicsearch |