Accession Number : ADA190409


Title :   A General Explanation-Based Learning Mechanism and Its Application to Narrative Understanding.


Descriptive Note : Technical rept.,


Corporate Author : ILLINOIS UNIV AT URBANA COORDINATED SCIENCE LAB


Personal Author(s) : Mooney, Raymond J


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a190409.pdf


Report Date : Dec 1987


Pagination or Media Count : 245


Abstract : Explanation-based learning (ELB) is a learning method which uses existing knowledge of the domain to construct an explanation for why a specific example is a member of a concept or why a specific combination of actions achieves a goal. This explanation is then generalized in an analytical manner in order to produce a general concept description or plan schema. Although a number of exploratory EBL systems which operate in particular domains have previously been constructed, recent research in this area lead to the development of general mechanisms which can perform explanation-based learning in a wide variety of domains. This thesis describes a general EBL mechanism, EGGS, which can make use of declarative knowledge stored in the form of horn clauses, rewrite rules, or STRIPS operators. Numerous examples are presented illustrating its application to a wide variety of domains, including 'blocks world' planning, logic circuit design. artifact recognition, and various forms of mathematical problem solving. The system is shown to improve its performance in each of these domains. Keywords: Artificial intelligence; Algorithms.


Descriptors :   *LEARNING , *LEARNING MACHINES , ALGORITHMS , ARTIFACTS , ARTIFICIAL INTELLIGENCE , EGGS , LOGIC CIRCUITS , MATHEMATICS , PROBLEM SOLVING , RECOGNITION , COGNITION , SCHEMATIC DIAGRAMS , NATURAL LANGUAGE


Subject Categories : Psychology
      Human Factors Engineering & Man Machine System


Distribution Statement : APPROVED FOR PUBLIC RELEASE