Adapting operator probabilities in genetic algorithms
Proceedings of the third international conference on Genetic algorithms
Probability Matching, the Magnitude of Reinforcement, and Classifier System Bidding
Machine Learning - Special issue on genetic algorithms
Finite-time Analysis of the Multiarmed Bandit Problem
Machine Learning
Proceedings of the 6th International Conference on Genetic Algorithms
A Racing Algorithm for Configuring Metaheuristics
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
An adaptive pursuit strategy for allocating operator probabilities
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Use of statistical outlier detection method in adaptive evolutionary algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Comparison-based algorithms are robust and randomized algorithms are anytime
Evolutionary Computation
Adapting operator settings in genetic algorithms
Evolutionary Computation
Adaptive operator selection with dynamic multi-armed bandits
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Parameter Setting in Evolutionary Algorithms
Parameter Setting in Evolutionary Algorithms
Relevance estimation and value calibration of evolutionary algorithm parameters
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Autonomous operator management for evolutionary algorithms
Journal of Heuristics
Comparison-based adaptive strategy selection with bandits in differential evolution
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Adaptive iterated local search for cross-domain optimisation
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Analyzing bandit-based adaptive operator selection mechanisms
Annals of Mathematics and Artificial Intelligence
Operator self-adaptation in genetic programming
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
From adaptive to more dynamic control in evolutionary algorithms
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
Multi-Objective differential evolution with adaptive control of parameters and operators
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
HyFlex: a benchmark framework for cross-domain heuristic search
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
Estimating meme fitness in adaptive memetic algorithms for combinatorial problems
Evolutionary Computation
A dynamic island model for adaptive operator selection
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Autoconstructive evolution for structural problems
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Adaptive operator selection at the hyper-level
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Adaptive evolutionary algorithms and extensions to the hyflex hyper-heuristic framework
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Vehicle routing and adaptive iterated local search within the hyflex hyper-heuristic framework
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
Autonomous local search algorithms with island representation
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
An adaptive evolutionary approach for real-time vehicle routing and dispatching
Computers and Operations Research
Non stationary operator selection with island models
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Credit Assignment is an important ingredient of several proposals that have been made for Adaptive Operator Selection. Instead of the average fitness improvement of newborn offspring, this paper proposes to use some empirical order statistics of those improvements, arguing that rare but highly beneficial jumps matter as much or more than frequent but small improvements. An extreme value based Credit Assignment is thus proposed, rewarding each operator with the best fitness improvement observed in a sliding window for this operator. This mechanism, combined with existing Adaptive Operator Selection rules, is investigated in an EC-like setting. First results show that the proposed method allows both the Adaptive Pursuitand the Dynamic Multi-Armed Banditselection rules to actually track the best operators along evolution.