Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
A connectionist machine for genetic hillclimbing
A connectionist machine for genetic hillclimbing
Learning Dominance Relations in Combined Search Problems
IEEE Transactions on Software Engineering
Genetic algorithms in noisy environments
Machine Language
Classifier systems and genetic algorithms
Machine learning: paradigms and methods
Intelligent mapping of communicating processes in distributed computing systems
Proceedings of the 1991 ACM/IEEE conference on Supercomputing
Intelligent process mapping through systematic improvement of heuristics
Journal of Parallel and Distributed Computing
Algorithms for combinatorial optimization in real-time and their automated refinements by genetics-based learning
CRIS: a test cultivation program for sequential VLSI circuits
ICCAD '92 Proceedings of the 1992 IEEE/ACM international conference on Computer-aided design
Load Balancing: An Automated Learning Approach
Load Balancing: An Automated Learning Approach
The Post-Game Analysis Framework-Developing Resource Management Strategies for Concurrent Systems
IEEE Transactions on Knowledge and Data Engineering
Population-Based Learning: A Method for Learning from Examples Under Resource Constraints
IEEE Transactions on Knowledge and Data Engineering
Learning Sequential Decision Rules Using Simulation Models and Competition
Machine Learning - Special issue on genetic algorithms
Case-Based Initialization of Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Temporal credit assignment in reinforcement learning
Temporal credit assignment in reinforcement learning
HITEC: a test generation package for sequential circuits
EURO-DAC '91 Proceedings of the conference on European design automation
A Framework for Learning in Search-Based Systems
IEEE Transactions on Knowledge and Data Engineering
Generalization and Generalizability Measures
IEEE Transactions on Knowledge and Data Engineering
Alternating Strategies for Sequential Circuit ATPG
EDTC '96 Proceedings of the 1996 European conference on Design and Test
Parallel Genetic Algorithms for Simulation-Based Sequential Circuit Test Generation
VLSID '97 Proceedings of the Tenth International Conference on VLSI Design: VLSI in Multimedia Applications
| Hi-index | 0.00 |
In this paper we present new methods for the automated learning of heuristics in knowledge-lean applications and for finding heuristics that can be generalized to unlearned domains. 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 cross-over. 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 three important issues in learning better heuristics: 1) anomalies in performance evaluation, 2) rational scheduling of limited computational resources in testing candidate heuristics in single-objective as well as multiobjective learning, and 3) finding heuristics that can be generalized to unlearned domains. We show experimental results in learning better heuristics for 1) process placement for distributed-memory multicomputers, 2) node decomposition in a branch-and-bound search, 3) generation of test patterns in VLSI circuit testing, and 4) VLSI cell placement and routing.