reinforcement learning

Levels of Autonomy in Robot-Assisted Laparoscopic Surgery: Current Capabilities and Evolutionary Pathways

The review concludes with the main barriers to clinical translation, including the sim-to-real gap, deformable tissue modeling, and safety and regulatory requirements, which show how embodied intelligence may influence future autonomous surgery in the operating room.

Comparing for the best: reinforcement learning for source citation identification with large language models

A reinforcement learning framework for energy-aware semiconductor manufacturing operations

Semiconductor manufacturing is among the most energy-intensive industrial activities because its production processes are highly complex, equipment is used at high levels, and operations must run continuously. In many traditional manufacturing settings, control strategies mainly aim at productivity—such as throughput,...

Computational Models of Emotion: A Brief Survey

Abstract Computational models of emotion (CMEs) have emerged as powerful tools for enabling the development of emotion-inspired intelligent artificial systems and advancing affective science by formalizing theories and enabling systematic experimentation. This chapter provides an overview of CMEs, examining their devel...

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...