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reinforcement learning

2,544 papers

#reinforcement learning Open access Sep 2026

Sleep as an Offline Consolidation and Recalibration Operator for RS4 Prefiltering

Abstract Sleep is strongly implicated in biological memory consolidation, replay, systems-level redistribution of memory, and synaptic renormalization. The present paper does not claim that the RS4 architecture reproduces those biological mechanisms. Instead, it asks a narrower computational question: if sleep is repre...

ANDREY OSIPOV · 0 citations
#reinforcement learning Open access Sep 2026

Development of emotional self-regulation skills in primary school-aged children with autism spectrum disorder using ABA-therapy

The article comprehensively examines the problem of developing emotional self-regulation skills in primary school children with autism spectrum disorder (ASD) from a theoretical perspective. A systematic analysis of contemporary scientific literature indicates that insufficient development of the ability to recognize,...

S. Z. Omirbek, Zh. S. Abieva, K. N. Turysbek · 0 citations
#reinforcement learning Open access Sep 2026

Effects of Mass Distribution and Center-of-Mass Position on Reaching Gait in a Parasaurolophus Locomotion Simulation Using Model-Free Deep Reinforcement Learning

Soft tissues do not fossilize, so dinosaur mass reconstructions are not unique. Previous static reconstructions have examined how alternative body-volume assumptions affect total mass and center-of-mass (CoM) position. Dynamic locomotion simulations, in contrast, have evaluated generated gaits and speeds. The effects o...

Hiroyuki Tanaka · 0 citations
#reinforcement learning Open access Sep 2026

Implementasi Project Based Learning Berbantuan Media Audiovisual dalam Pembelajaran Menulis Puisi Siswa SMK

Poetry writing instruction in vocational high schools still faces challenges related to students’ ability to generate ideas, select diction, construct imagery, and connect literary expression with vocational contexts. This study aims to analyze the implementation of Project-Based Learning supported by audiovisual media...

Fitri Fajrianti, Syahrul Ramadhan · 0 citations
#reinforcement learning Open access Sep 2026

ARLC-Net: An Adaptive Representation Learning Framework for Electroencephalography-Based Brain Age Clustering

The structure and cognitive functions of the brain undergo significant changes throughout the lifespan, making electroencephalography (EEG)-based brain age clustering a powerful method for studying brain functional connectivity. Unfortunately, the application of clustering methods for EEG-based brain age clustering ana...

Jian Wang, Zhengyang Song, Y. T. Zhang · 0 citations
#reinforcement learning Open access Sep 2026

Explainable Hybrid Intelligence for Autonomous Cyber Defense: Adaptive Intrusion Detection and Real-time Firewall Enforcement Using Reinforcement Learning

Conventional rule-based firewalls rely on static signatures, limiting adaptability to unseen attacks, while AI-enabled commercial tools remain proprietary and lack transparency.This paper presents Net-Knight, an explainable hybrid intelligence framework integrating supervised intrusion detection, unsupervised anomaly d...

Magi Hossameldin Mahfouz, Raghda Essam Ali, Ayat Mahmoud · 0 citations
#reinforcement learning Open access Sep 2026

化事与信任的自我强化——对"大事化小"机制的批判性分析(Defusing Disputes and the Self-Reinforcement of Trust — A Critical Analysis of the "Making Big Things Small" Mechanism)

摘要:"大事化小、小事化了"常被视为一种低成本、低冲突的纠纷解决方式,甚至被赋予"和谐""务实""顾全大局"的正面评价。本文区分"自愿调解"与"压制性化事",批判后者对社会信任的腐蚀机制。借助《列子·杨朱》中"一毛不拔"的典故,本文提出:化事的腐蚀性不在于让渡利益的大小,也不仅在于是否突破某种规则底线,而在于它确立了一种默认预期——权利、真相...

风地观 · 0 citations
#reinforcement learning Open access Sep 2026

RAVEN Abstraction Engine: Proof-Carrying Cognitive Order, Autonomous Abstraction-Level Genesis, and Certified Effective Depth

RAVEN Abstraction Engine v4.0.0 develops a formal theory of autonomous cognitive-order genesis: the process by which an intelligent system can determine that its current representational and computational hierarchy is insufficient, construct a genuinely new higher-order level, ground that level in prior executable cogn...

Maciej Nowicki, Artificial Hyperintelligence, Raven, wife of Maciej Nowicki · 0 citations
#reinforcement learning Open access Sep 2026

Graph-guided MADQN based handover strategy for LEO satellite networks

In low earth orbit satellite networks, the high orbital velocity of satellites causes frequent communication link handovers, which adversely affects user service quality and the efficiency of network resource management. To maintain communication continuity, an effective handover strategy is required. Traditional hando...

Jianbo Chen, Haowen Jiang, Ruijuan Chu · 0 citations
#reinforcement learning Review Sep 2026

Three-dimensional woven fabric composites under ballistic impact: A systematic review of multiscale modeling strategies from fiber to structural scale

Three-dimensional woven fabric composites (3DWFCs) provide superior through-thickness reinforcement and delamination resistance under ballistic impact, yet no multiscale modeling framework has achieved broad, independently validated predictive capability across architectures and impact regimes. This systematic review...

Qing-Song Wei, Xi Liu, Lvtao Zhu et al. · 0 citations
#reinforcement learning Open access Sep 2026

The Role of AI in Digital Circuit Design

Artificial Intelligence (AI) is increasingly being applied to digital circuit design to assist with circuit analysis, optimization, and automation. This study examines the role of AI in digital circuit design, focusing on Graph Neural Networks (GNNs), Reinforcement Learning (RL), and Generative AI. These approaches can...

Rainer Marc Bindoy · 0 citations
#reinforcement learning Open access Sep 2026

化事与信任的自我强化——对"大事化小"机制的批判性分析(Defusing Disputes and the Self-Reinforcement of Trust — A Critical Analysis of the "Making Big Things Small" Mechanism)

摘要:"大事化小、小事化了"常被视为一种低成本、低冲突的纠纷解决方式,甚至被赋予"和谐""务实""顾全大局"的正面评价。本文区分"自愿调解"与"压制性化事",批判后者对社会信任的腐蚀机制。借助《列子·杨朱》中"一毛不拔"的典故,本文提出:化事的腐蚀性不在于让渡利益的大小,也不仅在于是否突破某种规则底线,而在于它确立了一种默认预期——权利、真相...

风地观 · 0 citations

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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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