Cover Image

Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pawar, Urvi, Telangi, Kunal
Format:	Preprint
Published:	2025
Subjects:	Machine Learning I.2.6; I.2.8
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
by: Chapman, James, et al.
Published: (2025)

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
by: Tomashevskiy, Timofey
Published: (2026)

FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data
by: Pivezhandi, Mohammad, et al.
Published: (2024)

Are We Winning the Wrong Game? Revisiting Evaluation Practices for Long-Term Time Series Forecasting
by: Phungtua-eng, Thanapol, et al.
Published: (2026)

Regret-Aware Policy Optimization: Environment-Level Memory for Replay Suppression under Delayed Harm
by: Hiremath, Prakul Sunil
Published: (2026)

An Aircraft Upset Recovery System with Reinforcement Learning
by: Demir, Mahir, et al.
Published: (2026)

Predicting and improving test-time scaling laws via reward tail-guided search
by: Li, Muheng, et al.
Published: (2026)

Safe Reinforcement Learning with Preference-based Constraint Inference
by: Li, Chenglin, et al.
Published: (2026)

CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
by: Sauter, Andreas W. M., et al.
Published: (2024)

Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes
by: Wu, Xiaoyi, et al.
Published: (2025)

Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems
by: Nuzhin, Egor E., et al.
Published: (2024)

GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control
by: Hiremath, Prakul Sunil
Published: (2026)

StepScorer: Accelerating Reinforcement Learning with Step-wise Scoring and Psychological Regret Modeling
by: Xu, Zhe
Published: (2026)

Joint Combinatorial Node Selection and Resource Allocations in the Lightning Network using Attention-based Reinforcement Learning
by: Salahshour, Mahdi, et al.
Published: (2024)

Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
by: Silue, Bram, et al.
Published: (2025)

The Final-Stage Bottleneck: A Systematic Dissection of the R-Learner for Network Causal Inference
by: Sairam, S, et al.
Published: (2025)

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
by: Vincze, Mátyás, et al.
Published: (2024)

What Do World Models Learn in RL? Probing Latent Representations in Learned Environment Simulators
by: Zhang, Xinyu
Published: (2026)

Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
by: Riscos, Pablo de los, et al.
Published: (2024)

Adaptable Hindsight Experience Replay for Search-Based Learning
by: Vazaios, Alexandros, et al.
Published: (2025)

Machine Learning Based Path Planning for Improved Rover Navigation (Pre-Print Version)
by: Abcouwer, Neil, et al.
Published: (2020)

Differentiable Symbolic Planning: A Neural Architecture for Constraint Reasoning with Learned Feasibility
by: Oruganti, Venkatakrishna Reddy
Published: (2026)

An Automatic Ground Collision Avoidance System with Reinforcement Learning
by: Sevgili, Seyyid Osman, et al.
Published: (2026)

Social Interpretable Reinforcement Learning
by: Custode, Leonardo Lucio, et al.
Published: (2024)

Factored Diffusion Policies:Compositionally Generalized Robot Control with a Single Score Network
by: Mitra, Sayan, et al.
Published: (2026)

Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning
by: Wang, Zizhao, et al.
Published: (2024)

Dynamic Policy Induction for Adaptive Prompt Optimization: Bridging the Efficiency-Accuracy Gap via Lightweight Reinforcement Learning
by: Xu, Jiexi
Published: (2025)

Towards Systematic Generalization for Power Grid Optimization Problems
by: Memon, Zeeshan, et al.
Published: (2026)

Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning
by: Nägele, Maximilian, et al.
Published: (2024)

APC-GNN++: An Adaptive Patient-Centric GNN with Context-Aware Attention and Mini-Graph Explainability for Diabetes Classification
by: Berkani, Khaled
Published: (2025)

From Theory to Practice with RAVEN-UCB: Addressing Non-Stationarity in Multi-Armed Bandits through Variance Adaptation
by: Fang, Junyi, et al.
Published: (2025)

Embedded Safety-Aligned Intelligence via Differentiable Internal Alignment Embeddings
by: Rathva, Harsh, et al.
Published: (2025)

Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
by: Kang, Jiyeon, et al.
Published: (2025)

Bilinear Mamba-Koopman Neural MPC for Varying Dynamics
by: Pagi, Matan, et al.
Published: (2026)

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
by: Zawalski, Michał, et al.
Published: (2022)

Evolving machine learning workflows through interactive AutoML
by: Barbudo, Rafael, et al.
Published: (2024)

Incentives for Responsiveness, Instrumental Control and Impact
by: Carey, Ryan, et al.
Published: (2020)

On the Generalization Gap in LLM Planning: Tests and Verifier-Reward RL
by: Belcamino, Valerio, et al.
Published: (2026)

Not All Transitions Matter: Evidence from PPO
by: Basnet, Ajhesh
Published: (2026)