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We introduce Mix&Match (M&M) - a training framework designed to facilitate rapid and effective learning in RL agents, especially those that would be too slow or too challenging to train otherwise.
Jun 5, 2018
Abstract. We introduce Mix & Match (M&M) – a train- ing framework designed to facilitate rapid and effective learning in RL agents, especially those.
We introduce Mix&Match (M&M) - a training framework designed to facilitate rapid and effective learning in RL agents, especially those that would be too ...
[PDF] Mix & Match – Agent Curricula for Reinforcement Learning [Appendix]
proceedings.mlr.press › ...
In all experiments PBT controls adaptation of three hyper- parameters: α, learning rate and entropy cost regularisa- tion. We use populations of size 10.
Apr 29, 2023 · Curriculum learning is a training strategy in the context of DRL and other machine learning methods that involves organizing the learning process.
Missing: Mix&Match - | Show results with:Mix&Match -
Sukhbaatar et al. Curriculum Learning meets Reinforcement Learning. Page 15. Mix & Match –Agent Curricula for. Reinforcement Learning. Reverse Curriculum ...
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning. Qian Long, Zihan Zhou, Abhinav Gupta, Fei Fang, Yi Wu, Xiaolong Wang.
Jul 19, 2018 · • Mix & Match - Agent Curricula for Reinforcement Learning. • Learning to Explore via Meta-Policy Gradient. This one didn't make it to youtube ...
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In this paper, we propose a unified automatic curriculum learning framework to create multi-objective but coherent curricula that are generated by a set of ...
Apr 3, 2019 · Bibliographic details on Mix & Match Agent Curricula for Reinforcement Learning.