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Found 3 papers, 1 papers with code
Value-Aided Conditional Supervised Learning for Offline RL
Offline reinforcement learning (RL) has seen notable advancements through return-conditioned supervised learning (RCSL) and value-based methods, yet each approach comes with its own set of practical challenges.
LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework
In this paper, a unified framework for exploration in reinforcement learning (RL) is proposed based on an option-critic model.
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making
However, we discovered that the attention module of DT is not appropriate to capture the inherent local dependence pattern in trajectories of RL modeled as a Markov decision process.
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