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Automated design of knowledge-lean heuristics: Learning, resource scheduling, and generalization

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Title: Automated design of knowledge-lean heuristics: Learning, resource scheduling, and generalization
Author(s): Ieumwananonthachai, Arthur
Doctoral Committee Chair(s): Wah, Benjamin W.
Department / Program: Electrical and Computer Engineering
Discipline: Electrical and Computer Engineering
Degree Granting Institution: University of Illinois at Urbana-Champaign
Degree: Ph.D.
Genre: Dissertation
Subject(s): Engineering, Electronics and Electrical Artificial Intelligence Computer Science
Abstract: In this thesis we present new methods for the automated design of new heuristics in knowledge-lean applications and for finding heuristics that can be generalized to unlearned test cases. These applications lack domain knowledge for credit assignment; hence, operators for composing new heuristics are generally model free, domain independent, and syntactic in nature. The operators we have used are genetics based; examples of which include mutation and crossover. Learning is based on a generate-and-test paradigm that maintains a pool of competing heuristics, tests them to a limited extent, creates new ones from those that perform well in the past, and prunes poor ones from the pool. We have studied four important issues in learning better heuristics: (a) partitioning of a problem domain into smaller subsets, called subdomains, so that performance values within each subdomain can be evaluated statistically, (b) anomalies in performance evaluation within a subdomain, (c) rational scheduling of limited computational resources in testing candidate heuristics in single-objective as well as multi-objective learning, and (d) finding heuristics that can be generalized to unlearned sub domains.We show experimental results in learning better heuristics for (a) process placement for distributed-memory multicomputers, (b) node decomposition in a branch-and-bound search, (c) generation of test patterns in VLSI circuit testing, (d) VLSI cell placement and routing, and (e) blind equalization.
Issue Date: 1996
Type: Text
Language: English
URI: http://hdl.handle.net/2142/22817
ISBN: 9780591087147
Rights Information: Copyright 1996 Ieumwananonthachai, Arthur
Date Available in IDEALS: 2011-05-07
Identifier in Online Catalog: AAI9702544
OCLC Identifier: (UMI)AAI9702544
 

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