Accession Number : ADA296516
Title : Systematic Approach to the Design of Representation-Changing Algorithms.
Descriptive Note : Research rept.,
Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE
Personal Author(s) : Fink, Eugene
PDF Url : ADA296516
Report Date : FEB 1995
Pagination or Media Count : 34
Abstract : We explore methods for improving the performance of AI problem-solvers by automatically changing problem representations. The performance of all problem-solving systems depends crucially on problem representation. The same problem may be easy or difficult to solve depending on the way we describe it. Researchers have designed a variety of learning algorithms that deduce important information from the description of the problem domain and use the deduced information to improve the representation. Examples of these representation improvements include generating abstraction hierarchies, replacing operators with macros, and decomposing complex problems into subproblems. There has, however, been little research on the common principles underlying representation-improving algorithms and the notion of useful representation changes has remained at an informal level. We present preliminary results on a systematic approach to the design of algorithms for automatically improving representations. We identify the main desirable properties of such algorithms, present a framework for formally specifying these properties, and show how to implement a representation-improving algorithm based on the specification of its properties. We illustrate the use of this approach by developing novel algorithms that improve problem representations. (AN)
Descriptors : *ALGORITHMS, *PROBLEM SOLVING, *ARTIFICIAL INTELLIGENCE, OPTIMIZATION, AUTOMATION, COMPUTER AIDED DESIGN, SPECIFICATIONS, COMPUTER PROGRAMMING, ROBOTS, EFFICIENCY, INPUT OUTPUT PROCESSING, RULE BASED SYSTEMS, SYSTEMS ANALYSIS, CONTROL THEORY, HIERARCHIES, LEARNING, FIELDS(COMPUTER PROGRAMS).
Subject Categories : Computer Programming and Software
Distribution Statement : APPROVED FOR PUBLIC RELEASE