mlsanityData to 7 Oct 2026

Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration

arXiv 2006.01419 ↗First posted 2 Jun 2020cs.LG cs.AI stat.MLcited by 20

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Abstract (arXiv)

In this paper, sample-aware policy entropy regularization is proposed to enhance the conventional policy entropy regularization for better exploration. Exploiting the sample distribution obtainable from the replay buffer, the proposed sample-aware entropy regularization maximizes the entropy of the weighted sum of the policy action distribution and the sample action distribution from the replay buffer for sample-efficient exploration. A practical algorithm named diversity actor-critic (DAC) is developed by applying policy iteration to the objective function with the proposed sample-aware entropy regularization. Numerical results show that DAC significantly outperforms existing recent algorithms for reinforcement learning.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jun 2020.

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Citing papers per year: 2021: 2; 2022: 1; 2023: 4; 2024: 5; 2025: 7; 2026: 1.

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  1. 2021Adversarially Guided Actor-Criticcited by 47
  2. 2021A Max-Min Entropy Framework for Reinforcement Learningcited by 28
  3. 2023Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Criticcited by 20
  4. 2024ACE : Off-Policy Actor-Critic with Causality-Aware Entropy Regularizationcited by 16
  5. 2023Probabilistic Inference in Reinforcement Learning Done Rightcited by 11
  6. 2024AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classificationcited by 10
  7. 2024Exclusively Penalized Q-learning for Offline Reinforcement Learningcited by 8
  8. 2023LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Frameworkcited by 7
  9. 2025Self-Improving Skill Learning for Robust Skill-based Meta-Reinforcement Learningcited by 5
  10. 2023PAC-Bayesian Soft Actor-Critic Learningcited by 3
  11. 2024Learning Diverse Policies with Soft Self-Generated Guidancecited by 3
  12. 2025Off-policy Reinforcement Learning with Model-based Exploration Augmentationcited by 3
8 more
  1. 2025Learning Intractable Multimodal Policies with Reparameterization and Diversity Regularizationcited by 3
  2. 2026Retaining Suboptimal Actions to Follow Shifting Optima in Multi-Agent Reinforcement Learningcited by 3
  3. 2024Double Actor-Critic with TD Error-Driven Regularization in Reinforcement Learningcited by 2
  4. 2025Strict Subgoal Execution: Reliable Long-Horizon Planning in Hierarchical Reinforcement Learningcited by 1
  5. 2022Entropy Augmented Reinforcement Learningcited by 0
  6. 2025Enhance Exploration in Safe Reinforcement Learning with Contrastive Representation Learningcited by 0
  7. 2025HAEPO: History-Aggregated Exploratory Policy Optimizationcited by 0
  8. 2025Complexity-Regularized Proximal Policy Optimizationcited by 0