reinforcement learning

Analysis of Intelligent Privacy Protection Mechanisms for Smart Healthcare in the Context of the Internet of Things

In Internet of Things-based smart healthcare, while medical data sharing and model training are driving industry development, sensitive patient information is easily stolen and misused, and traditional data processing models struggle to balance security and usability. This research aims to construct an intelligent priv...

Multi-objective flexible job shop scheduling with worker-number decisions using preference-conditioned heterogeneous graph reinforcement learning

AI-Powered Crowdsourcing for Effective Disaster Relief Coordination: A Systematic Review

Post-disaster coordination is often hindered by information fragmentation. This paper reviews AI and crowdsourcing integration to address these challenges. We examine three core areas: situational awareness via text and geospatial data, logistics coordination using predictive modelling, and ethical deployment concerns....

Shaykh Abu H. Hasanoel Bashri's Method in Learning Fiqh: a Multi-Site Study in an Islamic Boarding School

This study aims to analyze the structure and implementation of fiqh (Islamic jurisprudence) learning methods within the pedagogical tradition of Sheikh Abu H. Hasanoel Bashri and to contribute to the development of fiqh pedagogy in dayah (traditional Islamic boarding schools). The study employs a qualitative approach w...

From Reactive Response to Proactive Mitigation: The Value of Precursor Risk Signals in DRL Inventory Control

Modern supply chains face abrupt supply disruptions, under which the stable lead time assumption behind conventional inventory control no longer holds. Most replenishment models, including existing deep reinforcement learning (DRL) formulations, act as feedback controllers. A disruption is treated as an unobservable ev...

Can a card-based educational game enhance functional anatomy knowledge in first-year medical students? A mixed-methods study

Anatomy is a foundational yet cognitively demanding subject in undergraduate medical education. Although game-based learning has shown potential to enhance engagement and assessment performance, evidence remains limited for low-cost, single-session, card-based interventions designed to reinforce functional anatomy. Thi...

Cooperative multi-agent reinforcement learning with entangled state representations and copula-based action coordination for urban navigation

The findings demonstrate that combining relational state representations, copula-based dependence modeling, and shared rewards improves coordination, robustness, and stability in multi-agent navigation tasks.

Machine Intelligence on the Edge: Interpretable Cardiac Pattern Localization Using Reinforcement Learning

Abstract Matched filters are widely used to localize signal patterns due to their high efficiency and interpretability. However, their effectiveness deteriorates for low signal-to-noise ratio (SNR) signals, such as those recorded on edge devices, where prominent noise patterns can closely resemble the target within the...

Distributional Reinforcement Learning on Path-dependent Options

Market Risk Prediction Model Based on Sentiment Factors and Deep Integration of Reinforcement Learning

Bit-compressed event-triggered fuzzy control for stochastic time-delay nonlinear systems via reinforcement learning

Deep Reinforcement Learning based Optimal Routing with Software-Defined Networking

An effective method for network congestion avoidance is to optimize the routing. We propose an optimalrouting controlling that combines Deep Reinforcement learning(DRL) based policy optimization andSoftware Defined Network(SDN) based flow control. It uses DRL to learn the optimal network routingpolicy in different traf...