reinforcement learning

From Programmed Execution to Autonomous Reasoning: The LLM-Driven Paradigm Shift in Air-Ground Collaborative Systems

This review critically examines how large language models (LLMs) and multimodal large language models (MLLMs) are reshaping the intelligence paradigm of air-ground heterogeneous collaborative systems between 2023 and 2026 and argues that the core of this transformation is a change in how AGCS understand tasks, coordina...

Formation control for multiple similar autonomous underwater vehicles with dynamic gaps via deep reinforcement learning

Dynamic gaps between simulation and real world environments are the major challenge for the implementation of deep reinforcement learning (RL) based formation control methods in systems composed of multiple similar autonomous underwater vehicles (AUVs), mainly involving hydrodynamic parameters and unknown disturbances....

Sequential Estimation of Remaining Useful Life Through VAE-Based Deep Reinforcement Learning With Reward Shaping

A novel framework that integrates Variational Autoencoders (VAE) as surrogate environments with actor-critic Deep Reinforcement Learning (DRL) to provide a modular and efficient sequential RUL estimation method for challenging industrial scenarios is introduced.

Federated PPO: Federated Proximal Policy Optimization for Multi-Robot Collision Avoidance

A Q-learning-based mobility-aware tree routing protocol in wireless body area networks

This study proposes a Q-learning-based mobility-aware tree routing protocol (QMTR) for WBANs integrated with vehicular ad hoc networks (VANETs) to support reliable transmission of passengers’ health data to remote medical centers.

A hierarchical spatio-temporal reinforcement learning framework for cooperative multi-USV search and interception

Multi-USV cooperative search and target interception holds value in maritime security, yet existing methods face three challenges: multi-timescale decision coupling, insufficient heterogeneous observation fusion, and inefficient exploration under sparse rewards. This paper proposes a multi-USV decision-making framework...

Optimization and Analysis of Agricultural Robot Drive Systems

This study takes the agricultural robot drive system as the research object and carries out optimization research from two dimensions: mechanical structure and intelligent control. At the mechanical level, redundant degrees of freedom are eliminated through topological analysis of mechanism freedom, a 'short-chain dire...

AI-Accelerated blockchain architecture for efficient and secure electronic healthcare record exchange

The AI-Accelerated Blockchain Architecture (AIBA-EHR), a framework engineered to accelerate transaction processing and enable adaptive security measures suitable for real-world clinical environments, is presented, indicating that the strategic fusion of artificial intelligence with distributed ledger technology can sim...

Intelligent Feeding Pattern Optimization in Aquaculture Using Deep Reinforcement Learning

Equity-Aware Planning of Urban Ultra-Fast Electric Vehicle Charging Infrastructure with Spatial Graph Learning and Grid Constraints

Urban ultra-fast-charging planning must connect equitable user service with physically deliverable charging power. This study formulates a heterogeneous graph linking demand zones, roads, candidate stations, and distribution buses, together with an infrastructure model for station locations, port-level power tiers, int...

Reinforcement learning-assisted walrus optimization algorithm for multi-equipment optimization in industrial cooling water systems

In industrial refrigeration plant cooling water systems, chillers, cooling water pumps, and cooling towers are strongly coupled, making independent equipment regulation insufficient for global optimality. Existing chiller plant control studies often insufficiently characterize cross time thermal coupling caused by cool...

The influence of a research-informed professional development course on Iranian in-service EFL teachers’ cognitions and reported practices regarding oral corrective feedback

Abstract This study examines the influence of a research-informed professional development (PD) course on Iranian in-service EFL teachers’ cognitions and reported practices regarding oral corrective feedback (OCF). Data were collected through pre- and post-course interviews, reflective diaries, and online discussions w...