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Page last updated: 2009-02-13
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| Files: | Description | File size | Format | |
| Fulltext Original |
146K | PDF (requires Acrobat Reader) | ||
| Fulltext 1st Revised |
197K | PDF (requires Acrobat Reader) | ||
| Fulltext 2nd Revised |
407K | PDF (requires Acrobat Reader) | ||
| Fulltext Original |
407K | PostScript (requires a PostScript Reader) | ||
| Fulltext 1st Revised |
651K | PostScript (requires a PostScript Reader) | ||
| Fulltext 2nd Revised |
793K | PostScript (requires a PostScript Reader) | ||
| Author: | David Poole | |||
| Article title: | Decision Theory, the Situation Calculus and Conditional Plans | |||
| Publ. type: | Article | |||
| Volume: | 3 | |||
| Article No: | 8 | |||
| Language: | English | |||
| Abstract [en]: | This paper shows how to combine decision theory and logical representations of actions in a manner that seems natural for both. In particular, we assume an axiomatization of the domain in terms of situation calculus, using what is essentially Reiter's solution to the frame problem, in terms of the completion of the axioms defining the state change. Uncertainty is handled in terms of the independent choice logic, which allows for independent choices and a logic program that gives the consequences of the choices. As part of the consequences are a specification of the utility of (final) states, and how (possibly noisy) sensors depend on the state. The robot adopts conditional plans, similar to the GOLOG programming language. Within this logic, we can define the expected utility of a conditional plan, based on the axiomatization of the actions, the sensors and the utility. Sensors can be noisy and actions can be stochastic. The planning problem is to find the plan with the highest expected utility. This representation is related to recent structured representations for partially observable Markov decision processes (POMDPs); here we use stochastic situation calculus rules to specify the state transition function and the reward/value function. Finally we show that with stochastic frame axioms, action representations in probabilistic STRIPS are exponentially larger than using the representation proposed here. | |||
| Note: | Info from author | |||
| Discussion: | Record of discussions about this article | |||
| Publisher: | Linköping University Electronic Press | |||
| Year: | 1998 | |||
| Available: | 1998-06-15 Original, 1st Revised 1999-03-17, 2nd Revised 11999-07-15 | |||
| No. of pages: | Original 43, 1st Revised 48 and 2nd Revised 39 | |||
| Series: | Linköping Electronic Articles in Computer and Information Science | |||
| ISSN: | 1401-9841 | |||
| Checksum PDF: | dbe43670c8a1c5be3bceaae2e485c4b7 /home/ep/www/ea/cis/1998/008/cis98008.pdf (MD5), Original | |||
| Checksum PDF: | [an error occurred while processing this directive] (MD5), 1st Revised | |||
| Checksum PDF: | 8dbd8688d24e4c33b9c5905fb86bf9c8 /home/ep/www/ea/cis/1998/008/cis98008-revise2.pdf (MD5), 2nd Revised | |||
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| Checksum PS: | 2bcf00781ef2c9075c4fd1763af0e8a1 /service/www-ep/docs/ea/cis/1998/008/cis98008-revised.ps (MD5), 1 st Revised | |||
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| PGP PDF: | PGP, Original | |||
| PGP PDF: | PGP, 1st Revised | |||
| PGP PDF | PGP, 2nd Revised | |||
| PGP PS: | PGP, Original | |||
| PGP PS: | PGP, 1st Revised | |||
| PGP PS: | PGP, 2nd Revised | |||
| Old Checksum: | Checksum (PS), Original | Information about recalculation of Checksum | |||
| Old Checksum: | Checksum (PS), 1st Revised | Information about recalculation of Checksum | |||
| Old Checksum: | Checksum (PS), 2nd Revised | Information about recalculation of Checksum | |||
| SPECIAL INFO: | Checksum, PGP and persistence | |||
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Last updated: 2009-02-13