Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Programming Challenges: The Programming Contest Training Manual
Programming Challenges: The Programming Contest Training Manual
PAC model-free reinforcement learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Reinforcement Learning: A Tutorial Survey and Recent Advances
INFORMS Journal on Computing
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Reinforcement learning for online control of evolutionary algorithms
ESOA'06 Proceedings of the 4th international conference on Engineering self-organising systems
Helper-objective optimization strategies for the Job-Shop Scheduling Problem
Applied Soft Computing
Generation of tests for programming challenge tasks using evolution algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Choosing Best Fitness Function with Reinforcement Learning
ICMLA '11 Proceedings of the 2011 10th International Conference on Machine Learning and Applications and Workshops - Volume 02
Generation of Tests for Programming Challenge Tasks on Graph Theory Using Evolution Strategy
ICMLA '12 Proceedings of the 2012 11th International Conference on Machine Learning and Applications - Volume 02
Adaptive Selection of Helper-Objectives with Reinforcement Learning
ICMLA '12 Proceedings of the 2012 11th International Conference on Machine Learning and Applications - Volume 02
ICMLA '12 Proceedings of the 2012 11th International Conference on Machine Learning and Applications - Volume 01
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In this paper, an evolutionary approach to generation of test cases for programming challenge tasks is investigated. Multi-objective and single-objective evolutionary algorithms, as well as helper-objective selection strategies, are compared. Particularly, a previously proposed method of choosing between helper-objectives with reinforcement learning is considered. This method is applied to the multi-objective evolutionary algorithm for the first time. Results of the experiment show that the most reasonable approach for the considered problem is using multi-objective evolutionary algorithm with automated helper-objective selection.