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Combining Associational and Causal Reasoning to Solve Interpretation and Planning Problems

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dc.creator Simmons, Reid G.
dc.date 2004-10-20T20:01:11Z
dc.date 2004-10-20T20:01:11Z
dc.date 1988-08-01
dc.date.accessioned 2013-10-09T02:47:12Z
dc.date.available 2013-10-09T02:47:12Z
dc.date.issued 2013-10-09
dc.identifier AITR-1048
dc.identifier http://hdl.handle.net/1721.1/6842
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description This report describes a paradigm for combining associational and causal reasoning to achieve efficient and robust problem-solving behavior. The Generate, Test and Debug (GTD) paradigm generates initial hypotheses using associational (heuristic) rules. The tester verifies hypotheses, supplying the debugger with causal explanations for bugs found if the test fails. The debugger uses domain-independent causal reasoning techniques to repair hypotheses, analyzing domain models and the causal explanations produced by the tester to determine how to replace faulty assumptions made by the generator. We analyze the strengths and weaknesses of associational and causal reasoning techniques, and present a theory of debugging plans and interpretations. The GTD paradigm has been implemented and tested in the domains of geologic interpretation, the blocks world, and Tower of Hanoi problems.
dc.format 215 p.
dc.format 20424253 bytes
dc.format 15960716 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AITR-1048
dc.subject associational reasoning
dc.subject causal reasoning
dc.subject planning
dc.subject sgeologic interpretation
dc.subject debugging
dc.title Combining Associational and Causal Reasoning to Solve Interpretation and Planning Problems


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