Acquiring (ir)relevance knowledge for problem solving
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abstract: A major drawback of artificial intelligence systems that rely on declarativerepresentations is that the efficiency of reasoning degrades quickly as thesize of the knowledge base increases. To address this problem when building asystem, we need to acquire not only knowledge about the domain, but alsoknowledge about the control of reasoning. In this paper, we discuss one typeof such control knowledge, namely, relevance of our knowledge to specificproblem solving goals. We show how this knowledge can be used by the problemsolver either to ignore part of its knowledge or to automatically createabstractions and how the system can guide the acquisition of such knowledge.We ground our discussion in a framework in which knowledge about relevance canbe stated, reasoned with and analyzed. We apply the framework to the problemof modeling physcial devices, where creating abstractions for a given task iscrucial in order to perform effective problem solving.
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| Abstract | A major drawback of artificial intelligenc … A major drawback of artificial intelligence systems that rely on declarativerepresentations is that the efficiency of reasoning degrades quickly as thesize of the knowledge base increases. To address this problem when building asystem, we need to acquire not only knowledge about the domain, but alsoknowledge about the control of reasoning. In this paper, we discuss one typeof such control knowledge, namely, relevance of our knowledge to specificproblem solving goals. We show how this knowledge can be used by the problemsolver either to ignore part of its knowledge or to automatically createabstractions and how the system can guide the acquisition of such knowledge.We ground our discussion in a framework in which knowledge about relevance canbe stated, reasoned with and analyzed. We apply the framework to the problemof modeling physcial devices, where creating abstractions for a given task iscrucial in order to perform effective problem solving. rder to perform effective problem solving. |
| Author | Alon Y. Halevy +, Yumi Iwasaki +, and Hiroshi Motoda + |
| Bibtype | techreport + |
| Institution | Knowledge Systems, AI Laboratory + |
| Key | KSL-92-46 + |
| Month | April + |
| Number | KSL-92-46 + |
| Tag | Computer science + |
| Title | Acquiring (Ir)relevance Knowledge for Problem solving + |
| Tr id | KSL-92-46 + |
| Year | 1992 + |
