Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Machine learning an artificial intelligence approach volume II
Machine learning an artificial intelligence approach volume II
Learning Dominance Relations in Combined Search Problems
IEEE Transactions on Software Engineering
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Applied multivariate statistical analysis
Applied multivariate statistical analysis
Classifier systems and genetic algorithms
Artificial Intelligence
Adaptive learning of decision-theoretic search control knowledge
Proceedings of the sixth international workshop on Machine learning
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
The cascade-correlation learning architecture
Advances in neural information processing systems 2
Artificial Intelligence - Special issue on knowledge representation
Intelligent mapping of communicating processes in distributed computing systems
Proceedings of the 1991 ACM/IEEE conference on Supercomputing
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Intelligent process mapping through systematic improvement of heuristics
Journal of Parallel and Distributed Computing
Steps toward artificial intelligence
Computers & thought
The Post-Game Analysis Framework-Developing Resource Management Strategies for Concurrent Systems
IEEE Transactions on Knowledge and Data Engineering
Learning Sequential Decision Rules Using Simulation Models and Competition
Machine Learning - Special issue on genetic algorithms
Genetic Algorithms in Noisy Environments
Machine Learning
Properties of the Bucket Brigade
Proceedings of the 1st International Conference on Genetic Algorithms
Performance Studies of Dynamic Load Balancing in Distributed Systems
Performance Studies of Dynamic Load Balancing in Distributed Systems
Temporal credit assignment in reinforcement learning
Temporal credit assignment in reinforcement learning
Genetics-Based Learning of New Heuristics: Rational Scheduling of Experiments and Generalization
IEEE Transactions on Knowledge and Data Engineering
Generalization and Generalizability Measures
IEEE Transactions on Knowledge and Data Engineering
Scheduling of genetic algorithms in a noisy environment
Evolutionary Computation
Constructing petri net models using genetic search
Mathematical and Computer Modelling: An International Journal
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A learning model for designing heuristics automatically under resource constraints is studied. The focus is on improving performance-related heuristic methods (HMs) in knowledge-lean application domains. It is assumed that learning is episodic, that the performance measures of an episode are dependent only on the final state reached in evaluating the corresponding test case, and that the aggregate performance measures of the HMs involved are independent of the order of evaluation of test cases. The learning model is based on testing a population of competing HMs for an application problem, and switches from one to another dynamically, depending on the outcome of previous tests. Its goal is to find a good HM within the resource constraints, with proper tradeoff between cost and quality. It extends existing work on classifier systems by addressing issues related to delays in feedback, scheduling of tests of HMs under limited resources, anomalies in performance evaluation, and scalability of HMs. Experience in applying the learning method is described.