The rapid growth of cloud data centres has increased their energy consumption and environmental footprint, highlighting the need for more energy-efficient resource management. Kubernetes has become a widely adopted container orchestration platform for automating the deployment, scaling, and management of containerized...
Megi Tartari, Genti Daci, Elinda Kajo Meçe· Ajakirjad. Journals by UT· 0 citations
Structured Episodic Memory (SEM) is an experimental non-neural agent architecture that combines overlapping state abstractions, associative value memories, eligibility-based temporal credit assignment, goal-conditioned contact control, and context-dependent strategy memory. We evaluate SEM in Pong using structured stat...
Berat Araç· Zenodo (CERN European Organi...· 0 citations
Code, aggregated data and provenance for the simulation campaign behind the manuscript. Twelve training seeds, twenty-five evaluation episodes per seed on a fixed shared evaluation base, four arms. Raw policy checkpoints and TensorBoard logs are not included: they exceed two gigabytes and every reported number is deriv...
Alina-Elena LUPULESCU, Monica Leba· Zenodo (CERN European Organi...· 0 citations
BRSDK is a deterministic, high-frequency telemetry framework and Python SDK designed to bridge the Simulation-to-Real (Sim2Real) transfer gap in autonomous vehicle engineering, reinforcement learning, and vehicle dynamics within BeamNG.drive and BeamNG.tech.
Kartikey Singh, BRSDK Contributors· Zenodo (CERN European Organi...· 0 citations
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This repository contains the code, data, and pre-trained models for "MulTADrug-GPT: A sample-efficient generative framework for multi-target drug design via reinforcement and preference learning". For detailed instructions on environment setup and the step-by-step execution of the training and evaluation pipelines, ple...
Anonymous· Zenodo (CERN European Organi...· 0 citations
This study proposes a compact rotary inverted pendulum experimental platform designed for implementing reinforcement learning (RL) based controllers on physical systems. While RL demonstrates superior performance in simulated environments, applying it to real-world systems often leads to performance degradation and ins...
Jaewook Lee, Doyoon Ju, Young‐Sam Lee· Journal of Institute of Cont...· 0 citations
A new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning is developed and a group-sparsity-based feature screening procedure is proposed that identifies, with high probability, a reduced feature set containing all relevant covariates.
The boundaries of how reinforcement learning optimizes the reasoning capabilities of large language models under different resource and scale constraints are reviewed, as well as the adaptability of reinforcement learning's optimization of large language models in different scenarios are analyzed.
Artificial Intelligence and Graph Theory Based Traffic Signal Control Systems for Road Intersections Traffic congestion is a critical and economically damaging problem in dense urban areas, driven by rapid urbanization, rising vehicle density, and — most critically — fixed-time signal strategies that fail to adapt to r...
Zavid Iqbal Bangalee, Deen Ahmed, Tanim Saleh Mahmud· Zenodo (CERN European Organi...· 0 citations
Artificial Intelligence and Graph Theory Based Traffic Signal Control Systems for Road Intersections Traffic congestion is a critical and economically damaging problem in dense urban areas, driven by rapid urbanization, rising vehicle density, and — most critically — fixed-time signal strategies that fail to adapt to r...
Zavid Iqbal Bangalee, Deen Ahmed, Tanim Saleh Mahmud· Zenodo (CERN European Organi...· 0 citations
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
Automated driving system (ADS) deployment requires rigorous validation across safety–critical vehicle–pedestrian interactions, yet real-world datasets rarely capture high-risk scenarios while simulation platforms lack realistic behavior. In response, this study proposes a three-stage framework that combines real-world...
Qian Pu, Kun Xie, Yuan Zhu et al.· Transportation Research Part...· 0 citations
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.
Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.
MIT News · Artificial Intelligence· news.mit.eduOct 27, 2026
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.
