AI Olympics challenge with Evolutionary Soft Actor Critic
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Abstract (arXiv)
In the following report, we describe the solution we propose for the AI Olympics competition held at IROS 2024. Our solution is based on a Model-free Deep Reinforcement Learning approach combined with an evolutionary strategy. We will briefly describe the algorithms that have been used and then provide details of the approach
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 10 references that are in the map. First posted on arXiv 2 Sep 2024.
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References · 4
- 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
- 2015Continuous control with deep reinforcement learningcited by 3,279
- 2021Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Applicationcited by 7
- 2023Solving the swing-up and balance task for the Acrobot and Pendubot with SACcited by 2
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