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Cited By

Instance Selection for Dynamic Algorithm Configuration with
Reinforcement Learning: Improving Generalization

Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization

18 July 2024

Gjorgjina Cenikj

Marius Lindauer

ArXiv (abs)PDF HTML Github

Papers citing "Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization"

2 / 2 papers shown

Deep Reinforcement Learning for Dynamic Algorithm Configuration: A Case Study on Optimizing OneMax with the (1+($λ$,$λ$))-GA

Deep Reinforcement Learning for Dynamic Algorithm Configuration: A Case Study on Optimizing OneMax with the (1+(

λ

λ

André Biedenkapp

123

1

0

03 Dec 2025

On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+($λ$,$λ$))-GA

On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(

λ

λ

))-GAAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2025

André Biendenkapp

362

4

0

27 Feb 2025

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