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reinforcement learning

2,335 papers

#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
#reinforcement learning Dataset Open access Sep 2026

This dataset supports the paper "Cardinality-Adaptive Multi-Agent Reinforcement Learning for Variable-Scale Cooperative Aerial Games"

This dataset supports the paper "Cardinality-Adaptive Multi-Agent Reinforcement Learning for Variable-Scale Cooperative Aerial Games" (submitted to Applied Intelligence). It contains the complete training and evaluation records of CA-MAPPO, a cardinality-adaptive multi-agent proximal policy optimization algorithm for v...

mavyn chown · 0 citations
#reinforcement learning Open access Sep 2026

Decision-Relative Observation Quotients for Sequential Control

This paper studies when a reinforcement-learning system should acquire additional information before acting. It introduces causal observability: a finite criterion for whether an observation regime preserves the intervention-relevant distinctions needed for a declared decision. The central result shows that observation...

Kaliel Williamson · 0 citations
#reinforcement learning Open access Sep 2026

Regime-Aware Reinforcement Learning: A Mixture-of-Experts Framework for Dynamic Asset Allocation

Recent advances in reinforcement learning (RL) have spurred growing interest in its application to multi-period financial planning. Existing literature broadly follows three paradigms: hybrid RL, scalable RL, and end-to-end RL. This paper develops a hybrid regime-aware RL framework for dynamic asset allocation that emb...

Yirui Luo, John M. Mulvey · 0 citations

From tech blogs

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Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

MIT News · Artificial Intelligence Oct 7, 2026

Discovering the value of humanistic inquiry

Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.

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