Reinforcement Learning Based Acceptance Criteria for Metaheuristic Algorithms
Abstract This paper proposes novel reinforcement learning-based acceptance criteria for metaheuristic algorithms. We develop Q-learning and Deep Q-learning-based acceptance criteria and integrate them into simulated annealing (SA) and artificial bee colony (ABC) algorithms. Also, we design two versi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-025-00924-2 |
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