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reinforcement learning

2,609 papers

#reinforcement learning Open access Sep 2026

Transfer Is a Directed Relation: Four Quantities Under One Word in the Cross-Domain RLVR Debate, and Why the Structural-Similarity Reading Does Not Survive Its Own Evidence

(c) 2026 Pranay Mahendrakar. Licensed under CC BY 4.0. Reinforcement learning with verifiable rewards is the standard route to reasoning-tuned language models, and the field has split over whether its gains leave the training domain. One body of work reports that most models succeeding at mathematics fail to transfer a...

Pranay M. Mahendrakar · 0 citations
#reinforcement learning Open access Sep 2026

Supplemental Materials for "Constrained Reinforcement Learning Scheduling for Low-Carbon IES Considering P2G-CCS Coupling and District Heating Network Thermal Inertia"

This record contains the supplemental materials associated with the manuscript entitled “Constrained Reinforcement Learning Scheduling for Low-Carbon IES Considering P2G-CCS Coupling and District Heating Network Thermal Inertia.” The supplemental materials include standard SAC update equations, the complete Action Proj...

Zhang Hao, Lan Sheng · 0 citations
#reinforcement learning Open access Sep 2026

Adaptive Digital Signal Processing with Reinforcement Learning

This paper presents a novel approach to digital signal processing (DSP) utilizing reinforcement learning (RL). Traditional DSP algorithms are frequently designed with static parameters, rendering them ineffective when faced with dynamic or non-stationary signals. The proposed method leverages RL to train a DSP algorith...

Jincheng Zhang · 0 citations
#reinforcement learning Dataset Open access Sep 2026

"Physics-Informed Distributed Model Predictive Control for Thermally Aware Energy Management in AI Data centers"

"This dataset and reproducibility package accompanies the research paper \"Physics-Informed Distributed Model Predictive Control for Thermally Aware Energy Management in Hyperscale Artificial Intelligence Data Centers,\" provisionally accepted as a Regular Paper in the IEEE Transactions on Industrial Informatics (Paper...

Mohamed Taha · 0 citations
#reinforcement learning Open access Sep 2026

Dynamic Graph Optimization Algorithm

Existing graph optimization algorithms are fundamentally static, failing to adapt effectively to the inherent dynamic nature of graph structures. This paper introduces a novel Dynamic Graph Optimization Algorithm (DGOTA) designed to address this limitation. The core of DGOTA leverages Reinforcement Learning (RL) to tra...

Jincheng Zhang · 0 citations
#reinforcement learning Open access Sep 2026

Supplemental Materials for "Constrained Reinforcement Learning Scheduling for Low-Carbon IES Considering P2G-CCS Coupling and District Heating Network Thermal Inertia"

This record contains the supplemental materials associated with the manuscript entitled “Constrained Reinforcement Learning Scheduling for Low-Carbon IES Considering P2G-CCS Coupling and District Heating Network Thermal Inertia.” The supplemental materials include standard SAC update equations, the complete Action Proj...

Zhang Hao, Lan Sheng · 0 citations
#reinforcement learning Open access Sep 2026

Adaptive Resource Management Based on Reinforcement Learning

This paper investigates the application of adaptive reinforcement learning (RL) for efficient hardware resource management. Traditional hardware resource management often relies on static configurations and manual tuning, which can be inefficient and unresponsive to dynamic workloads. This research proposes a novel app...

Jincheng Zhang · 0 citations
#reinforcement learning Open access Sep 2026

Self-Organizing Quantum Hardware via Adaptive Entanglement Control

This paper presents a novel approach to quantum hardware design and control, leveraging reinforcement learning to achieve self-organization and optimal performance. The core concept is that quantum processors, rather than relying on pre-determined calibration, can dynamically adapt their entanglement generation and mai...

Jincheng Zhang · 0 citations
#reinforcement learning Open access Sep 2026

Deep Graph Reinforcement Learning with Hierarchical Policy Learning

This paper presents a novel approach to Deep Graph Reinforcement Learning (DGRL) that leverages hierarchical policy learning to enhance both sample efficiency and learning speed. Traditional DGRL methods often suffer from slow exploration and high computational demands, particularly when dealing with large, complex gra...

Jincheng Zhang · 0 citations
#reinforcement learning Open access Sep 2026

THE DOLGUN MODEL FROM INDIVIDUAL TO SOCIETY Transferring the Micro- and Macro-Cycles to the Collective Level, and a Proposed Synthetic– Empirical Research Programme / BİREYDEN TOPLUMA DOLGUN MODELİ Mikro ve Makro Çevrimlerin Toplumsal Düzleme Aktarımı ve Sınanabilir Bir Sentetik– Ampirik Araştırma Programı Önerisi

AbstractThis study establishes the transfer of the individually specified Dolgun Model to the collective level andproposes a complementary programme of synthetic and empirical experiments through which thattransfer can be tested. It is not a findings paper: no simulation has been run, no data collected and noresults re...

Ahmet Burak Dolgun · 0 citations
#reinforcement learning Dataset Open access Sep 2026

A Quantum-Inspired Dragonfly Optimization and Deep Reinforcement Learning Framework for Energy-Efficient Routing in Ad Hoc and IoT Networks

This repository presents QADO-DRL, a novel energy-efficient routing framework for wireless ad hoc and IoT networks that combines Quantum-Inspired Adaptive Dragonfly Optimization (QADO) with a Dueling Double Deep Q-Network (D3QN) routing agent. QADO uses quantum-superposition initialization and quantum rotation-gate upd...

P. Senthilkumar · 0 citations
#reinforcement learning Open access Sep 2026

Inferential learning explains association between self-relevance cues and overlap in chimpanzee visual bodily gesture repertoires

We investigated whether the association of self-relevance cues with overlap in visual bodily gestures is better explained by inferential learning or experience-based reinforcement of gesture–outcome contingencies. Inferential accounts predict that self-relevance cues facilitate convergence by supporting goal inference...

Anna Ilona Roberts, Piotr Sorokowski, Sam G. B. Roberts · 0 citations

From tech blogs

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Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

Google DeepMind Blog Nov 3, 2026

Agentic cheminformatics with Google Antigravity

Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.

MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

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