Lei Han

MHER: Model-based Hindsight Experience Replay

2021 · arXiv (Cornell University)

Solving multi-goal reinforcement learning (RL) problems with sparse rewards is generally challenging. Existing approaches have utilized goal relabeling on collected experiences to alleviate issues raised from sparse rewards. However, these methods are still limited in …

Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent

2024 · arXiv (Cornell University)

We propose HyperAgent, a reinforcement learning (RL) algorithm based on the hypermodel framework for exploration in RL. HyperAgent allows for the efficient incremental approximation of posteriors associated with an optimal action-value function ($Q^\star$) without the …

Deep Reinforcement Learning Based Scheduling Strategy in Blockchain Payment Channel Networks

2024 · IEEE Transactions on Networking

With the popularity of blockchains, low transaction throughput has become a significant bottleneck in applications such as cryptocurrencies. Payment channel networks (PCNs) have received attention as a way to improve throughput. However, due to the …