Adaptive Transformers in RL
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Abstract (arXiv)
Recent developments in Transformers have opened new interesting areas of research in partially observable reinforcement learning tasks. Results from late 2019 showed that Transformers are able to outperform LSTMs on both memory intense and reactive tasks. In this work we first partially replicate the results shown in Stabilizing Transformers in RL on both reactive and memory based environments. We then show performance improvement coupled with reduced computation when adding adaptive attention span to this Stable Transformer on a challenging DMLab30 environment. The code for all our experiments and models is available at https://github.com/jerrodparker20/adaptive-transformers-in-rl.
Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Apr 2020.
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Citing papers per year: 2021: 4; 2022: 1; 2023: 4; 2024: 1; 2025: 3.
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- 2021Offline Reinforcement Learning as One Big Sequence Modeling Problemcited by 636
- 2021Pathologies in priors and inference for Bayesian transformerscited by 13
- 2022Explain My Surprise: Learning Efficient Long-Term Memory by Predicting Uncertain Outcomescited by 11
- 2021Provably Improved Context-Based Offline Meta-RL with Attention and Contrastive Learningcited by 2
- 2023Learning Computational Efficient Bots with Costly Featurescited by 2
- 2024Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learningcited by 2
- 2021Lyapunov-based uncertainty-aware safe reinforcement learningcited by 1
- 2023Deep Generative Models for Decision-Making and Controlcited by 1
- 2023Sample-based Dynamic Hierarchical Transformer with Layer and Head Flexibility via Contextual Banditcited by 1
- 2023Neural architecture impact on identifying temporally extended Reinforcement Learning taskscited by 0
- 2025Diverse Transformer Decoding for Offline Reinforcement Learning Using Financial Algorithmic Approachescited by 0
- 2025Learning to Focus: Prioritizing Informative Histories with Structured Attention Mechanisms in Partially Observable Reinforcement Learningcited by 0
- 2025Large Language Models and 3D Vision for Intelligent Robotic Perception and Autonomy14 Nov 2025
- 2025Learning to Focus: Prioritizing Informative Histories with Structured Attention Mechanisms in Partially Observable Reinforcement Learning10 Nov 2025
- 2025Diverse Transformer Decoding for Offline Reinforcement Learning Using Financial Algorithmic Approaches13 Feb 2025
- 2024Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learning12 Nov 2024
- 2023Sample-based Dynamic Hierarchical Transformer with Layer and Head Flexibility via Contextual Bandit5 Dec 2023
- 2023Neural architecture impact on identifying temporally extended Reinforcement Learning tasks4 Oct 2023
- 2023Learning Computational Efficient Bots with Costly Features18 Aug 2023
- 2023Deep Generative Models for Decision-Making and Control15 Jun 2023
- 2022Explain My Surprise: Learning Efficient Long-Term Memory by Predicting Uncertain Outcomes27 Jul 2022
- 2021Pathologies in priors and inference for Bayesian transformers8 Oct 2021
- 2021Lyapunov-based uncertainty-aware safe reinforcement learning29 Jul 2021
- 2021Offline Reinforcement Learning as One Big Sequence Modeling Problem3 Jun 2021
- 2021Provably Improved Context-Based Offline Meta-RL with Attention and Contrastive Learningcited by 2
- 2023Learning Computational Efficient Bots with Costly Featurescited by 2
- 2024Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learningcited by 2
- 2025Diverse Transformer Decoding for Offline Reinforcement Learning Using Financial Algorithmic Approachescited by 0
- 2025Diverse Transformer Decoding for Offline Reinforcement Learning Using Financial Algorithmic Approaches13 Feb 2025
- 2024Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learning12 Nov 2024
- 2023Learning Computational Efficient Bots with Costly Features18 Aug 2023
- 2021Provably Improved Context-Based Offline Meta-RL with Attention and Contrastive Learning22 Feb 2021
- 2021Pathologies in priors and inference for Bayesian transformerscited by 13
- 2022Explain My Surprise: Learning Efficient Long-Term Memory by Predicting Uncertain Outcomescited by 11
- 2021Lyapunov-based uncertainty-aware safe reinforcement learningcited by 1
- 2023Deep Generative Models for Decision-Making and Controlcited by 1
- 2023Sample-based Dynamic Hierarchical Transformer with Layer and Head Flexibility via Contextual Banditcited by 1
- 2023Neural architecture impact on identifying temporally extended Reinforcement Learning taskscited by 0
- 2025Large Language Models and 3D Vision for Intelligent Robotic Perception and Autonomycited by 0
- 2025Large Language Models and 3D Vision for Intelligent Robotic Perception and Autonomy14 Nov 2025
- 2023Sample-based Dynamic Hierarchical Transformer with Layer and Head Flexibility via Contextual Bandit5 Dec 2023
- 2023Neural architecture impact on identifying temporally extended Reinforcement Learning tasks4 Oct 2023
- 2023Deep Generative Models for Decision-Making and Control15 Jun 2023
- 2022Explain My Surprise: Learning Efficient Long-Term Memory by Predicting Uncertain Outcomes27 Jul 2022
- 2021Pathologies in priors and inference for Bayesian transformers8 Oct 2021
- 2021Lyapunov-based uncertainty-aware safe reinforcement learning29 Jul 2021