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• A New Framework for Multi-Agent Reinforcement Learning -- Centralized Training and Exploration with Decentralized Execution via Policy Distillation
  2019 · 28 citations
• An Adaptive Clipping Approach for Proximal Policy Optimization
  2018 · 25 citations
• Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization
  2018 · 8 citations
• Off-Policy Actor-Critic in an Ensemble: Achieving Maximum General Entropy and Effective Environment Exploration in Deep Reinforcement Learning
  2019 · 5 citations
• Merging Deterministic Policy Gradient Estimations with Varied Bias-Variance Tradeoff for Effective Deep Reinforcement Learning
  2019 · 2 citations
• Decorrelated Double Q-learning
  2020 · 2 citations
• Multi-Agent Deep Reinforcement Learning for Request Dispatching in Distributed-Controller Software-Defined Networking
  2021 · 2 citations
• Context-aware Active Multi-Step Reinforcement Learning