Accession Number : ADA292206

Title :   Management of Speedup Mechanisms in Learning Architectures.

Descriptive Note : Doctoral's thesis,

Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE

Personal Author(s) : Cheng, John

PDF Url : ADA292206

Report Date : JAN 1995

Pagination or Media Count : 167

Abstract : Learning architectures typically operate rather inefficiently. To increase performance, two strategies are commonly used: speedup mechanisms are incorporated into the architecture, and architecture operation is simplified. Unfortunately, both these strategies have drawbacks. Because of the utility problem, inappropriate use of speedup mechanisms can actually decrease system efficiency. Hence, good speedup mechanism management - deciding when, where, and which speedup mechanism to use - is important if the mechanisms are to be effective. Typically, however, good management strategies are not available. Architecture-provided strategies are usually very simple, and cannot use the mechanisms appropriately all the time. Good user-provided strategies are also difficult to develop - under a complex system or domain, it can be difficult to understand system behavior well enough to specify a good management strategy. Furthermore, user or architecture-provided management techniques are usually fixed, and cannot adapt to environment dynamics. Hence, lack of good management strategies limit the effectiveness of speedup mechanisms.

Descriptors :   *COMPUTER ARCHITECTURE, *EFFICIENCY, *SYSTEMS APPROACH, *LEARNING, ALGORITHMS, SYSTEMS ENGINEERING, ENVIRONMENTS, STRATEGY, MANAGEMENT, DYNAMICS, THESES, LIMITATIONS, OPERATION, EMBEDDING, ARTIFICIAL INTELLIGENCE.

Subject Categories : Computer Programming and Software

Distribution Statement : APPROVED FOR PUBLIC RELEASE