Complete lattice computation of Wilson loop expectation values under SU(3) gauge theory on a four-dimensional Euclidean lattice. Establishes color confinement via the area law and extracts the non-perturbative Yang-Mills mass gap of 77.71 MeV from the two-point glueball correlator spectral decomposition. ⚖️ PROPRIETARY...
Dimitar Stavrev Prodromov· Zenodo (CERN European Organi...· 0 citations
Overview This is the initial public release of the code associated with the paper "Image-Based Reinforcement Learning for Robust Mode Hop Recovery in External-Cavity Diode Lasers." The repository provides a simulation and reinforcement-learning framework for recovering an external-cavity diode laser from mode hops usin...
Jaeick Bae, Kyoungsik Yu, Yunheung Song et al.· Zenodo (CERN European Organi...· 0 citations
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. Contains the game engine, 26 agents spanning hand-written heuristics, metaheuristic tuning, PIMC and single- and multiple...
Emergency Vehicle Preemption (EVP) can substantially reduce response times during urban emergencies, yet
aggressive green-wave strategies often induce severe secondary congestion on competing approaches and prolong network
recovery. This paper presents a communication-aware Multi-Agent Proximal Policy Optimization (MAP...
Sara Tazeen, Sudhakara A. M.· International Journal of Inn...· 0 citations
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This repository provides the research software, reproducibility materials, benchmark results, and figure-generation resources accompanying the study “Adaptive Anchor-Guided Spherical-Neutrosophic Intelligence for Uncertainty-Aware Engineering Systems.” The package implements and supports the proposed Adaptive Anchor-Gu...
Rana Amirova· Zenodo (CERN European Organi...· 0 citations
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· Zenodo (CERN European Organi...· 0 citations
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...
Setti Sarika, S. Jhansi Rani· International journal of int...· 0 citations
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.
Xin Xia, Xi-Hong Fei, Kang Wang et al.· Structural Health Monitoring· 0 citations
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...
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...
Ladgrad Ladislav Gradečak· Zenodo (CERN European Organi...· 0 citations
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.