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reinforcement learning

2,442 papers

VirtuAI-Safe: Personalized Situated Safety Learning through Integration of VR and LLMs

Construction safety outcomes are strongly shaped by human factors, including how individuals perceive hazards, interpret contextual cues, and make safety-related decisions in dynamic work environments. Safety education therefore plays a critical role in preparing future construction professionals to reason about risk...

Ali Katooziani, R. Jayasinghe, Idris Jeelani et al. · 0 citations
#reinforcement learning Open access Oct 2026

Integrating Remote Sensing, Multi-Objective Optimization, and Agent-Based Modelling for Nature-Based Flood Mitigation

By 2030, pluvial flooding is estimated to cause nearly $500 billion in global damage, affecting 54 million people (UNDRR, 2015) each year. By 2050, metropolitan assets worth around $158 trillion could be at risk of floods. This rising risk has sparked an increased interest in nature-based solutions (NbS), as traditiona...

Yashashvi Agrawal, Marcos Navarrete Pardo, Eleni Ntagkouli et al. · 0 citations
#reinforcement learning Open access Oct 2026

Emergence Conditions and Robustness Verification of Minimal Self-Awareness: A Systematic Study Based on Controlled Ablation Experiments

Abstract The origin of self-awareness is a fundamental issue at the intersection of cognitive science and artificial intelligence. Existing studies mostly focus on the operating mechanisms of higher-order consciousness, and lack systematic controlled experimental verification of the emergence conditions for the most ba...

Jiye Huang, Jizhang Huang · 0 citations
#reinforcement learning Open access Oct 2026

Baselines, Sample Size, and Supervisory Activity in Guarded Reinforcement-Learning Traffic Signal Control: A SUMO Evidence Audit

Guarded supervision may leave a learned adviser inactive, obscuring non-inferiority. We audited an eight-version yellowSimulation of Urban MObility (SUMO) program covering three networks and 3480 counterfactual pairs. A contrast model gained 16.38 percentage points of root-mean-square-error skill over zero effect; eigh...

Mikhail G. Gorodnichev, Marina S. Moseva · 0 citations
#reinforcement learning Open access Oct 2026

Gas-Flow-Rate Control Method of Solid-Rocket Ramjet Engines Based on Deep-Reinforcement Learning

The solid-rocket ramjet is a promising and critical propulsion component for propulsion systems in hypersonic vehicles. However, the gas-flow regulation system of the solid-rocket ramjet exhibits strong nonlinearity, time-varying parameters and abrupt operating-condition changes, which makes it challenging to design a...

Heng Deng, Yang Liu, Kun Jiang · 0 citations
#reinforcement learning Open access Oct 2026

Sustainable Approaches to Corrosion Protection in Reinforced Concrete: A Critical Review of Green Inhibitors, Surface Treatments, Self-Healing Systems, Nanomaterials, Smart Coatings, and Life-Cycle-Based Design

Corrosion of steel reinforcement is still the main reason reinforced concrete structures fail before the end of their planned service life. Every early repair costs money, and it also adds new cement, steel, and emissions. This review examines protection methods that can extend service life while lowering environmental...

Md Arifuzzaman, Ziad Nayef Shatnawi, Abdullah Al Mamun et al. · 0 citations
#reinforcement learning Open access Oct 2026

A Diamond Grain Lost in the Sandy River Bank - The Illusion of Wisdom in the Age of AI, Data Truncation, and the Erasure of Absolute Truth

This concept paper bridges classical Theravada Buddhist epistemological frameworks with mathematical information theory to diagnose a fundamental structural flaw in contemporary artificial intelligence alignment paradigms. Utilizing the classical allegory of the Nakhasikha Sutta—the comparison between a few sand grains...

Maung Maung Saw · 0 citations
#reinforcement learning Open access Oct 2026

Adaptive Self-Reinforcement and Mutual Reinforcement in World Self-and-Mutual Models: A Unified Architecture for Switching Between Independent and Interdependent World-Model Evolution

World models provide internal representations of environmental states, dynamics, and potential future outcomes. However, improving a world model can follow different learning regimes. A model may improve independently through its own prediction errors, internal consistency checks, counterfactual simulation, and interac...

Jincheng Zhang · 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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