An Overview of Causal Reasoning

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Citation: P. Pandurang Nayak. (1989) An Overview of Causal Reasoning. In KSL-89-27, June,1989.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author P. Pandurang Nayak
title An Overview of Causal Reasoning
number KSL-89-27
institution Knowledge Systems, AI Laboratory
year 1989
month June
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abstract In recent years, causal reasoning has begun to play an increasingly important role in Artificial Intelligence. It has been used in a number of different application areas including medicine, digital circuits, and engineering systems. Causal reasoning systems stand in contrast to most current expert systems that are based on empirical associations. In most expert systems, the expert knowledge base typically consists of a set of rules that specify appropriate actions for a number of situations (called situation-action rules). These rules are usually culled from the experience of domain experts and reflect empirical associations between the situations and the appropriate actions. Causal reasoning systems take a different view to building knowledge bases. Instead of representing specific situation-action rules, causal reasoning systems represent the underlying causal knowledge in the domain. This causal knowledge is used for problem-solving and the specific situation-action rules are, in some sense, derivable from it. In this paper we provide an overview of the literature on causal reasoning.

KSL Technical Report ID: KSL-89-27
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Abstract In recent years, causal reasoning has begu … In recent years, causal reasoning has begun to play an increasingly important role in Artificial Intelligence. It has been used in a number of different application areas including medicine, digital circuits, and engineering systems. Causal reasoning systems stand in contrast to most current expert systems that are based on empirical associations. In most expert systems, the expert knowledge base typically consists of a set of rules that specify appropriate actions for a number of situations (called situation-action rules). These rules are usually culled from the experience of domain experts and reflect empirical associations between the situations and the appropriate actions. Causal reasoning systems take a different view to building knowledge bases. Instead of representing specific situation-action rules, causal reasoning systems represent the underlying causal knowledge in the domain. This causal knowledge is used for problem-solving and the specific situation-action rules are, in some sense, derivable from it. In this paper we provide an overview of the literature on causal reasoning. iew of the literature on causal reasoning.
Author P. Pandurang Nayak  +
Bibtype techreport  +
Has author P. Pandurang Nayak  +
Has identifier KSL-89-27  +
Has publishing details June,1989  +
Has title An Overview of Causal Reasoning  +
Has where published KSL-89-27  +
Has year 1989  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-89-27  +
Month June  +
Number KSL-89-27  +
Process note NO  +
Title An Overview of Causal Reasoning  +
Year 1989  +
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