An augmented friction model that incorporates the Stribeck effect to capture the low-velocity nonlinearities characteristic of high-gear-ratio actuators and indicates that explicitly modeling low-velocity friction is beneficial for high-fidelity sim-to-real transfer in high-reduction systems.
Hansol Kang, Hyunyong Lee, Jiman Park et al.· Machines· 0 citations
This study proposes a source-study-aware validation framework to estimate the shear capacity of stirrup-free steel-fiber-reinforced concrete corbels and assess the reliability and generalizability of machine-learning models in structural engineering. A database of 108 specimens, compiled from seven independent studies,...
This study aims to identify the factors causing students' learning difficulties in History and to describe the teacher's role in helping tenth-grade students overcome these learning difficulties at MA Negeri Insan Cendekia Palu. This research employed a descriptive qualitative approach. The participants consisted of th...
Alvina Dewiyanti· Journal of Education and Tea...· 0 citations
Procrastination is widespread, costly, and persistent despite strong intentions to change. We show how procrastination can arise in stationary environments, where there are no deadlines, changing incentives, or new information to justify delay. With hyperbolic discounting, stochastic delay, i.e., acting with a fixed pr...
Yonatan Loewenstein, Dražen Prelec, H. Sebastian Seung· bioRxiv (Cold Spring Harbor...· 0 citations
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Regression testing in continuous integration (CI) helps preserve delivered software value by exposing regressions early, but limited feedback windows make test order consequential. This study evaluates a leakage-safe dynamic test case prioritization framework that reconstructs job–build–commit provenance, combines stri...
Overview This preprint presents the Autonomous Transduction Machine (ATM), a computational system that translates the Primitive Architecture of Spiral Geometry into an executable autonomous kernel capable of acting, constructing, learning, and self-correcting without fine human supervision. The architecture reproduces,...
Cláudio Vicente da Silva· Zenodo (CERN European Organi...· 0 citations
In Chapter 2 , we explored the pivotal shift from rigid automation to the era of intelligent machines, introducing AI and Machine Learning, particularly Reinforcement Learning, as the core technologies enabling robots to learn. We learned that humanoids could begin to “see” and “learn to walk” through these advancement...
Ahmed Olabisi Olajide· River Publishers eBooks· 0 citations
Urban rail transit systems face a pronounced contradiction between escalating traction energy consumption and passenger service quality under the carbon peaking and carbon neutrality goals. This study proposes a hybrid optimization framework offline combining deep reinforcement learning (DRL) and Non-dominated Sorting...
This release corresponds to the code used for the manuscript: "Reinforcement learning discovers new mechanisms of reentry in excitable media" The repository contains code for cellular automaton simulations, reinforcement-learning environments and training scripts, policy evaluation, simulations in the geometries studie...
Thomas Bury· Zenodo (CERN European Organi...· 0 citations
This package contains the extended test results for my Bachelor thesis MineAgent: Deep Reinforcement Learning-based Testing for Minecraft at the University of Trento, supervised by Fondazione Bruno Kessler (FBK) researchers.
Tommaso Parlato· Zenodo (CERN European Organi...· 0 citations
Code associated with the manuscript “Reinforcement learning discovers new mechanisms of reentry in excitable media.” This archive corresponds to the current manuscript submission and includes the cellular automaton simulations, reinforcement-learning environments and training scripts, policy evaluation, simulations in...
Thomas Bury, Glisant Plasa, José Miguel Romero Sepúlveda et al.· Zenodo (CERN European Organi...· 0 citations
A modular framework for rolling-horizon operational control using a Gym-compatible agent–environment abstraction. The framework enables integration of optimization-based agents (Pyomo), reinforcement learning agents (Stable-Baselines3), heuristic search methods, and rule-based controllers. Environments can be instantia...
Andreas Clément, Jerome Stock, Julius Nicholas Balzer et al.· Zenodo (CERN European Organi...· 0 citations
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
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.
MIT News · Artificial Intelligence· news.mit.eduOct 7, 2026
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.
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