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2,547 papers
A control-plane analysis distinguishing three concepts routinely collapsed in contemporary AI discourse: event verifiability, proxy validity, and governance sufficiency. Taking Reinforcement Learning with Self-Verifiable Rewards and its SpyRL instantiation as its case, it accepts the engineering contribution — an envir...
This chapter explores the transformative role of artificial intelligence (AI) and machine learning (ML) in modern healthcare and medical training. We first outline the rapid progress of AI, fueled by the digitization of health data and advances in computing, which has led to significant shifts in how clinical data and...
This paper investigates the output-feedback inverse reinforcement learning (IRL) problem and proposes a data-driven output-feedback off-policy inverse Q-learning algorithm that relies solely on input–output trajectory data from an expert system to address the problem of an unknown performance index in discrete-time lin...
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This work states that there has been an upsurge of interest and development of RL theory and applications in the communities of stochastic control, stochastic analysis and unsupervised learning.
Heating, Ventilation, and Air Conditioning (HVAC) systems account for 60–70% of residential electricity consumption in Oman, where extreme desert climate, with temperatures regularly exceeding 45 °C create substantial cooling demands. Unlike general reviews of smart HVAC controls, this study specifically evaluates the...
A comprehensive extraction grid covering the 21 selected primary studies. Synthesizes structural data including author, publication venue, process mining domain, reinforcement learning approach, and explainability (XAI) focus.
A comprehensive extraction grid covering the 21 selected primary studies. Synthesizes structural data including author, publication venue, process mining domain, reinforcement learning approach, and explainability (XAI) focus.
This study is intended to serve as a structured reference for the development of scalable, trustworthy, and intelligent IoV systems by highlighting state-of-the-art techniques, open research gaps, and future directions.
This repository contains the complete data, code, trained models, intermediate outputs, robustness checks, and figures supporting the manuscript “Regime-Aware Reinforcement Learning for Inflation Forecast Combination in Sub-Saharan Africa.” The empirical dataset covers eight Sub-Saharan African economies—Côte d’Ivoire,...
This mixed-methods study examined the effectiveness of Instagram Reels and traditional flashcards as vocabulary learning interventions for teaching vocabulary to first-year English as a Second Language (ESL) undergraduates at a Sri Lankan state university. Grounded in Cognitive Load Theory, Dual Coding Theory, and Mult...
In recent years, Unmanned Aerial Vehicles (UAVs) have gradually been widely used in various fields such as regional search and disaster relief, and the development of related technologies has also experienced unprecedented growth. Compared to individual UAVs, the collaborative execution of tasks by UAV swarms has more...
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.
Education Innovation
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
A Blog post by NVIDIA on Hugging Face
A Blog post by IBM Research on Hugging Face
A new machine-learning approach broke records for weather forecasting for an important time frame in emergency planning.
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