Category
2,152 papers
First public release, accompanying the manuscript "Search-based agents outperform reinforcement learning in Dahal Jeet, a Nepali imperfect-information card game", under review at Scientific Reports. Dahal Jeet is a four-player partnership trick-taking game played across the Terai-Madhesh region of Nepal in which only t...
As system decentralization heterogeneous resource constraints and the uncertain threat against quantum computing are introduced by rapid growth of edge-cloud computing infrastructures, this develop also raises new security challenges.Traditional security architectures depend on stationary cryptographic deployments and...
A novel multi-scale physics-informed neural network with enhanced reinforcement learning (MPINN-ERL) for bearing fault diagnosis under data scarcity and achieves competitive diagnostic accuracy.
First public release, accompanying the manuscript "Search-based agents outperform reinforcement learning in Dahal Jeet, a Nepali imperfect-information card game", under review at Scientific Reports. Dahal Jeet is a four-player partnership trick-taking game played across the Terai-Madhesh region of Nepal in which only t...
Reach audiences
Advertise in front of researchers, engineers, and readers.
Kratki opisStručni usporedni rad analizira funkcionalni položaj PREDECISION™ arhitekture u odnosu na safety filtering, reinforcement-learning shielding i runtime assurance. Naglasak je na razlikovanju determinističke kvalifikacije već generiranog ili odabranog kandidata od mehanizama koji modificiraju, zamjenjuju ili p...
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...
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,...
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...
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...
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...
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...
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...
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.
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.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
The effort aims to help U.S. learners from kindergarten to community college, with an emphasis on math, making, and the constructive use of AI.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
