Real-Time Recurrent Learning using Trace Units in Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Elelimy, Esraa, White, Adam, Bowling, Michael, White, Martha |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Rethinking the Foundations for Continual Reinforcement Learning
by: Elelimy, Esraa, et al.
Published: (2025)
by: Elelimy, Esraa, et al.
Published: (2025)
Deep Reinforcement Learning with Gradient Eligibility Traces
by: Elelimy, Esraa, et al.
Published: (2025)
by: Elelimy, Esraa, et al.
Published: (2025)
AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning
by: Pramanik, Subhojeet, et al.
Published: (2023)
by: Pramanik, Subhojeet, et al.
Published: (2023)
A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
by: Adkins, Jacob, et al.
Published: (2024)
by: Adkins, Jacob, et al.
Published: (2024)
Investigating the Histogram Loss in Regression
by: Imani, Ehsan, et al.
Published: (2024)
by: Imani, Ehsan, et al.
Published: (2024)
Empirical Design in Reinforcement Learning
by: Patterson, Andrew, et al.
Published: (2023)
by: Patterson, Andrew, et al.
Published: (2023)
A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning
by: Patterson, Andrew, et al.
Published: (2021)
by: Patterson, Andrew, et al.
Published: (2021)
Forager: a lightweight testbed for continual learning with partial observability in RL
by: Tang, Steven, et al.
Published: (2026)
by: Tang, Steven, et al.
Published: (2026)
A New View on Planning in Online Reinforcement Learning
by: Roice, Kevin, et al.
Published: (2024)
by: Roice, Kevin, et al.
Published: (2024)
Value Bonuses using Ensemble Errors for Exploration in Reinforcement Learning
by: Wahab, Abdul, et al.
Published: (2026)
by: Wahab, Abdul, et al.
Published: (2026)
Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence
by: Zhu, Lingwei, et al.
Published: (2023)
by: Zhu, Lingwei, et al.
Published: (2023)
Fine-Tuning without Performance Degradation
by: Wang, Han, et al.
Published: (2025)
by: Wang, Han, et al.
Published: (2025)
Harnessing Discrete Representations For Continual Reinforcement Learning
by: Meyer, Edan, et al.
Published: (2023)
by: Meyer, Edan, et al.
Published: (2023)
When is Offline Policy Selection Sample Efficient for Reinforcement Learning?
by: Liu, Vincent, et al.
Published: (2023)
by: Liu, Vincent, et al.
Published: (2023)
On the Interplay Between Sparsity and Training in Deep Reinforcement Learning
by: Davelouis, Fatima, et al.
Published: (2025)
by: Davelouis, Fatima, et al.
Published: (2025)
Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning
by: Schlegel, Matthew, et al.
Published: (2026)
by: Schlegel, Matthew, et al.
Published: (2026)
Mitigating Value Hallucination in Dyna Planning via Multistep Predecessor Models
by: Aminmansour, Farzane, et al.
Published: (2020)
by: Aminmansour, Farzane, et al.
Published: (2020)
Investigating the Interplay of Prioritized Replay and Generalization
by: Panahi, Parham Mohammad, et al.
Published: (2024)
by: Panahi, Parham Mohammad, et al.
Published: (2024)
Gradient Iterated Temporal-Difference Learning
by: Vincent, Théo, et al.
Published: (2026)
by: Vincent, Théo, et al.
Published: (2026)
Revisiting Mixture Policies in Entropy-Regularized Actor-Critic
by: He, Jiamin, et al.
Published: (2026)
by: He, Jiamin, et al.
Published: (2026)
Demystifying the Recency Heuristic in Temporal-Difference Learning
by: Daley, Brett, et al.
Published: (2024)
by: Daley, Brett, et al.
Published: (2024)
Proper Laplacian Representation Learning
by: Gomez, Diego, et al.
Published: (2023)
by: Gomez, Diego, et al.
Published: (2023)
Minion Gated Recurrent Unit for Continual Learning
by: Zyarah, Abdullah M., et al.
Published: (2025)
by: Zyarah, Abdullah M., et al.
Published: (2025)
Human-Inspired Multi-Level Reinforcement Learning
by: Wu, Mingkang, et al.
Published: (2025)
by: Wu, Mingkang, et al.
Published: (2025)
An Analysis of Action-Value Temporal-Difference Methods That Learn State Values
by: Daley, Brett, et al.
Published: (2025)
by: Daley, Brett, et al.
Published: (2025)
Recurrent Reinforcement Learning with Memoroids
by: Morad, Steven, et al.
Published: (2024)
by: Morad, Steven, et al.
Published: (2024)
Robust Real-Time Mortality Prediction in the Intensive Care Unit using Temporal Difference Learning
by: Frost, Thomas, et al.
Published: (2024)
by: Frost, Thomas, et al.
Published: (2024)
Learning to Be Cautious
by: Mohammedalamen, Montaser, et al.
Published: (2021)
by: Mohammedalamen, Montaser, et al.
Published: (2021)
Performance Optimization of Ratings-Based Reinforcement Learning
by: Rose, Evelyn, et al.
Published: (2025)
by: Rose, Evelyn, et al.
Published: (2025)
Rating-based Reinforcement Learning
by: White, Devin, et al.
Published: (2023)
by: White, Devin, et al.
Published: (2023)
Handling Delay in Real-Time Reinforcement Learning
by: Anokhin, Ivan, et al.
Published: (2025)
by: Anokhin, Ivan, et al.
Published: (2025)
Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
by: Zhao, Yike, et al.
Published: (2026)
by: Zhao, Yike, et al.
Published: (2026)
Goal-Space Planning with Subgoal Models
by: Lo, Chunlok, et al.
Published: (2022)
by: Lo, Chunlok, et al.
Published: (2022)
Optimizing Life Sciences Agents in Real-Time using Reinforcement Learning
by: Chadderwala, Nihir
Published: (2025)
by: Chadderwala, Nihir
Published: (2025)
Deep Double Q-learning
by: Nagarajan, Prabhat, et al.
Published: (2025)
by: Nagarajan, Prabhat, et al.
Published: (2025)
Distributions as Actions: A Unified Framework for Diverse Action Spaces
by: He, Jiamin, et al.
Published: (2025)
by: He, Jiamin, et al.
Published: (2025)
Safe Offline Reinforcement Learning with Real-Time Budget Constraints
by: Lin, Qian, et al.
Published: (2023)
by: Lin, Qian, et al.
Published: (2023)
Recurrent Deep Reinforcement Learning for Chemotherapy Control under Partial Observability
by: Kiram, Firas Mohamed Elamine, et al.
Published: (2026)
by: Kiram, Firas Mohamed Elamine, et al.
Published: (2026)
GPU Memory Requirement Prediction for Deep Learning Task Based on Bidirectional Gated Recurrent Unit Optimization Transformer
by: Wang, Chao, et al.
Published: (2025)
by: Wang, Chao, et al.
Published: (2025)
The Cross-environment Hyperparameter Setting Benchmark for Reinforcement Learning
by: Patterson, Andrew, et al.
Published: (2024)
by: Patterson, Andrew, et al.
Published: (2024)
Similar Items
-
Rethinking the Foundations for Continual Reinforcement Learning
by: Elelimy, Esraa, et al.
Published: (2025) -
Deep Reinforcement Learning with Gradient Eligibility Traces
by: Elelimy, Esraa, et al.
Published: (2025) -
AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning
by: Pramanik, Subhojeet, et al.
Published: (2023) -
A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
by: Adkins, Jacob, et al.
Published: (2024) -
Investigating the Histogram Loss in Regression
by: Imani, Ehsan, et al.
Published: (2024)