Cover Image

Demystifying the Recency Heuristic in Temporal-Difference Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Daley, Brett, Machado, Marlos C., White, Martha
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An Analysis of Action-Value Temporal-Difference Methods That Learn State Values
by: Daley, Brett, et al.
Published: (2025)

Deep Reinforcement Learning with Gradient Eligibility Traces
by: Elelimy, Esraa, et al.
Published: (2025)

Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
by: Daley, Brett, et al.
Published: (2024)

Deep Double Q-learning
by: Nagarajan, Prabhat, et al.
Published: (2025)

Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning
by: Daley, Brett, et al.
Published: (2023)

Harnessing Discrete Representations For Continual Reinforcement Learning
by: Meyer, Edan, et al.
Published: (2023)

AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning
by: Pramanik, Subhojeet, et al.
Published: (2023)

Solving Freshness in RAG: A Simple Recency Prior and the Limits of Heuristic Trend Detection
by: Grofsky, Matthew
Published: (2025)

Gradient Iterated Temporal-Difference Learning
by: Vincent, Théo, et al.
Published: (2026)

Proper Laplacian Representation Learning
by: Gomez, Diego, et al.
Published: (2023)

The Laplacian Keyboard: Beyond the Linear Span
by: Chandrasekar, Siddarth, et al.
Published: (2026)

Recency Biased Causal Attention for Time-series Forecasting
by: Hegazy, Kareem, et al.
Published: (2025)

The Cell Must Go On: Agar.io for Continual Reinforcement Learning
by: Mohamed, Mohamed A., et al.
Published: (2025)

Temporal-Difference Variational Continual Learning
by: Melo, Luckeciano C., et al.
Published: (2024)

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning
by: Patterson, Andrew, et al.
Published: (2021)

Real-Time Recurrent Learning using Trace Units in Reinforcement Learning
by: Elelimy, Esraa, et al.
Published: (2024)

Empirical Design in Reinforcement Learning
by: Patterson, Andrew, et al.
Published: (2023)

Discerning Temporal Difference Learning
by: Ma, Jianfei
Published: (2023)

Backstepping Temporal Difference Learning
by: Lim, Han-Dong, et al.
Published: (2023)

Enhancing Knowledge Tracing through Leakage-Free and Recency-Aware Embeddings
by: Badran, Yahya, et al.
Published: (2025)

Demystifying MuZero Planning: Interpreting the Learned Model
by: Guei, Hung, et al.
Published: (2024)

No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism
by: Li, Yubo, et al.
Published: (2025)

Value Bonuses using Ensemble Errors for Exploration in Reinforcement Learning
by: Wahab, Abdul, et al.
Published: (2026)

Fine-Tuning without Performance Degradation
by: Wang, Han, et al.
Published: (2025)

A Variance Minimization Approach to Temporal-Difference Learning
by: Chen, Xingguo, et al.
Published: (2024)

Is Temporal Difference Learning the Gold Standard for Stitching in RL?
by: Bortkiewicz, Michał, et al.
Published: (2025)

Temporal Difference Flows
by: Farebrother, Jesse, et al.
Published: (2025)

A New View on Planning in Online Reinforcement Learning
by: Roice, Kevin, et al.
Published: (2024)

An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models
by: Pan, Yangchen, et al.
Published: (2024)

Rethinking the Foundations for Continual Reinforcement Learning
by: Elelimy, Esraa, et al.
Published: (2025)

Model Collapse Demystified: The Case of Regression
by: Dohmatob, Elvis, et al.
Published: (2024)

Finite-Time Analysis of Temporal Difference Learning with Experience Replay
by: Lim, Han-Dong, et al.
Published: (2023)

Deep Reinforcement Learning and The Tale of Two Temporal Difference Errors
by: Rojas, Juan Sebastian, et al.
Published: (2026)

Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence
by: Zhu, Lingwei, et al.
Published: (2023)

When is Offline Policy Selection Sample Efficient for Reinforcement Learning?
by: Liu, Vincent, et al.
Published: (2023)

Learning Admissible Heuristics for A*: Theory and Practice
by: Futuhi, Ehsan, et al.
Published: (2025)

Almost Sure Convergence of Linear Temporal Difference Learning with Arbitrary Features
by: Wang, Jiuqi, et al.
Published: (2024)

Finite Sample Analysis of Linear Temporal Difference Learning with Arbitrary Features
by: Xie, Zixuan, et al.
Published: (2025)

Cochain Perspectives on Temporal-Difference Signals for Learning Beyond Markov Dynamics
by: Zhang, Zuyuan, et al.
Published: (2026)

Shortcut to Nowhere: Demystifying Deep Spurious Regression
by: Xu, Guanrong, et al.
Published: (2026)