reinforcement learning

AI-Powered Logic Gate Optimization for Efficient Electronic Design

Abstract The continuous development of modern electronic devices has resulted in increasingly complex Integrated Circuits (ICs). As the number of logic gates and circuit components increases, designing efficient electronic systems becomes more challenging. Engineers need to consider several important factors, including...

Gamification and NLP

Integrating gamification and advanced natural language processing (NLP) offers promising avenues to enhance literary education and student engagement, particularly within India's linguistically diverse context. The proposed study designs and analyses an AI-based gamified literary role-playing experience to encourage le...

Deep reinforcement learning based optimal control for wave energy converters: practical implementation and experimental validation

Ocean wave energy resources are immense and, if harnessed, can serve as a reliable source to support a significant portion of electricity needs. However, the technology to convert wave power into useful electrical power is still cost-intensive. One significant challenge is inefficient Power Take-Off (PTO) control techn...

Coordinated Offloading Cooperative Multi-Agent Reinforcement Learning for the Edge–Cloud Continuum

The increasing demand for intelligent, low-latency services in edge–cloud continuum systems poses new challenges for dynamic and efficient task offloading. We propose a Multi Agent Reinforcement Learning (MARL) framework for dis tributed task offloading under partial observability, where each device offloads only a por...

THE EFFECT of USING PID INTERACTIVE MEDIA on CRITICAL THINKING SKILLS of GRADE V STUDENTS at SD NEGERI 4 SUKAJAWA

This study examines the effectiveness of Digital Interactive Boards (DIB) in fostering critical thinking skills among fifth-grade elementary school students. The central premise of this investigation stems from the persistent gap between the availability of technological infrastructure in educational settings and its s...

Multi-Objective Intelligent Optimization of Excavation and Support for Super-Large Cross-Section Small Clear Spacing Tunnels in Urban Sensitive Areas: An Integrated Study of Numerical Simulation and Machine Learning

Coastal subsea tunnels often traverse shallow heterogeneous strata, creating significant deformation risks. Deformation control is therefore essential for safe urban construction. This study integrates FLAC3D, SSA-LSSVM, and NSGA-II for multi-objective excavation-support optimization. The Qingdao Jiaozhou Bay Second Su...

Artificial intelligence for scanning probe microscopy: from data analysis to autonomous experimentation

Advanced scanning probe microscopy (SPM) measurements have traditionally required highly specialized skills, but the integration of artificial intelligence (AI) and machine learning has begun to transform how SPM is operated. This review surveys AI methods applied to SPM, organized by technique rather than chronology:...

Responding to Health Equity Crises in Underserved Populations

Health equity crises—surges in maternal mortality, infectious disease outbreaks, chronic disease decompensation, and behavioral health emergencies that disproportionately affect low-income, rural, tribal, and minority communities—continue to outpace the capacity of conventional public health resource allocation systems...

What Does the Reward Pay For? An Empirical Study of Reward Hacking and Reward Design in Reinforcement Learning for Unit Test Generation

Adaptive moral compass framework for ethical reasoning and self-oversight in autonomous AI agents

The growing use of autonomous artificial intelligence agents in high-risk areas such as -driving cars, medical triage tools, military robots, and disaster-response drones, has made AI ethics an important concern for researchers. Current alignment methods, especially Reinforcement Learning from Human Feedback, have show...

Hierarchical Adaptive Sliding Mode Control with Deep Reinforcement Learning for Solar-Assisted Fuel Cell Hybrid Electric Vehicles

This repository contains the MATLAB files associated with the paper entitled “Hierarchical Adaptive Sliding Mode Control with Deep Reinforcement Learning for Solar-Assisted Fuel Cell Hybrid Electric Vehicles.” The deposited files support the numerical simulations and performance evaluation reported in the manuscript. T...

Hybrid Artificial Intelligence Integrating Deep Learning and Reinforcement Learning