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reinforcement learning

2,613 papers

#reinforcement learning Open access Aug 2026

Neuromorphic Computing with Spike-Timing Dependent Plasticity (STDP) for Reinforcement Learning

This paper explores the application of neuromorphic computing principles, specifically utilizing Spike-Timing Dependent Plasticity (STDP), for enhancing reinforcement learning (RL) performance. Traditional deep learning approaches often struggle with sparse reward environments, requiring extensive training and substant...

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

A Reinforcement Learning-Assisted ADMM Framework for Peer-to-Peer Kilowatt and Negawatt Trading with Cloud Energy Storage

Rooftop solar lets households generate their own electricity, but the benefits are unevenly shared and home batteries are expensive. This thesis develops a system that lets neighbours trade electricity, and reductions in their energy use, directly with one another, while sharing a common pool of storage instead of buyi...

Ezzeldin Ayman Ibrahim Ismail · 0 citations
#reinforcement learning Open access Aug 2026

Title: Self-Organizing Constraint Networks for Dynamic Data Structures

This paper introduces a novel approach to data structure design leveraging Self-Organizing Constraint Networks (SOCN). SOCN networks dynamically reorganize themselves based on observed data patterns, offering a highly adaptable solution for a wide range of applications. We propose a reinforcement learning framework to...

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

Multi-Objective Task Allocation and Path Planning in Heterogeneous Multi-Robot Systems Using Hierarchical Framework and Reinforcement Learning

This study proposes a multi-objective optimization framework for task allocation and path planning in transport-oriented multi-robot systems. The framework explicitly considers heterogeneous robot capabilities and load capacities while jointly minimizing task completion time and overall energy consumption. A hierarchic...

Sheng-Hsiang Luo, Rongshun Chen · 0 citations
#reinforcement learning Open access Aug 2026

Adaptive Quantum State Measurement and Information Extraction

This paper investigates the development of an adaptive quantum state measurement protocol designed to enhance information extraction efficiency from quantum states while mitigating the detrimental effects of decoherence. The core idea revolves around employing a reinforcement learning algorithm to dynamically adjust th...

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

Dynamic Symbolic Regression with Evolutionary Reinforcement Learning

This paper presents a novel approach to symbolic regression, termed Dynamic Symbolic Regression with Evolutionary Reinforcement Learning (DSR-ERL). The core idea is to leverage reinforcement learning (RL) to dynamically control an evolutionary algorithm, specifically optimizing the mutation and crossover operators with...

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

Hierarchical Reinforcement Learning with Intrinsic Motivation and Meta-Learning

This paper proposes a novel hierarchical reinforcement learning (HRL) framework that leverages intrinsic motivation, meta-learning, and a hierarchical architecture to address the limitations of traditional HRL methods concerning exploration and generalization. The core idea is to integrate these three components to cre...

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

Adaptive Graph Theory Algorithm

This paper introduces a novel self-adaptive graph theory algorithm designed to optimize the performance of machine learning algorithms through dynamic graph structure adjustment. Traditional graph theory algorithms often operate on static graphs, failing to adequately leverage the inherent variability in data and task...

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

Dynamic Neuro-Morphic Network Architecture Adaptation

This paper presents a novel approach to designing neuro-morphic networks capable of adapting to dynamic and complex input data. The core idea revolves around mimicking the inherent plasticity and evolving connectivity observed in biological neural networks. We introduce a reinforcement learning-based algorithm that con...

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

Multi-Agent Collaborative Learning with Dynamic Topology Optimization

This paper addresses the challenge of optimizing multi-agent collaborative learning (MCL) by introducing a dynamic topology structure optimization framework. Traditional MCL methods often rely on fixed topologies, which may not be optimal for varying task demands and evolving agent states. We propose a novel approach t...

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

The Human Brain in the Age of Uncertainty: Adaptive Neurocognitive Mechanisms and Human Behavior in the Contemporary Environment

This final project examines how adaptive neurocognitive mechanisms related to threat detection, uncertainty processing, anticipation, reward learning, social comparison, belonging, metacognition, and behavioral regulation interact with characteristics of contemporary environments. The study adopts a theoretical and int...

Thiago Campos Silva · 0 citations
#reinforcement learning Open access Aug 2026

Dynamic Topological Adaptive Neural Architecture Search

This paper proposes a novel approach to Neural Architecture Search (NAS) termed Dynamic Topological Adaptive NAS (DTANAS), which leverages concepts from topological data analysis and physical systems to achieve more efficient and robust architecture optimization. The core idea is to model the search space as a complex...

Jincheng Zhang · 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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