reinforcement learning

Reinforcement Learning with Value of Perfect Information Exploration

From Greedy Steps to Global Optimization: Learning Sequential Test Suite Generation

With the rapid evolution of Large Language Models (LLMs), automated software testing is witnessing a paradigm shift. While proprietary models like GPT-4o demonstrate impressive capabilities, their high deployment costs and data privacy concerns make open-source LLMs the practical imperative for many academic and indust...

Cultural Homogenisation in Artificial Intelligence and Social Media: The Role of Annotator Labour Bias and Global Consequences

The rapid growth of artificial intelligence (AI) and social media platforms has revolutionized global communication and creativity; however, it has also amplified concerns about cultural homogenization. These technologies are largely dominated by Western companies, which infuse cultural biases into AI frameworks and th...

A Closer Look at the Use of Reinforcement Learning for Speeding Up Runtime Verification of Software Tests (Experience Paper)

Runtime verification (RV) found many bugs by monitoring passing tests against formal specifications (specs), but it is slow. A recent work, Valg, used reinforcement learning (RL) to speed up RV by up to 551.5x or 27 hours. Valg aims to probabilistically monitor most unique traces—sequences of spec-related events like m...

HIC-DRL: A deep reinforcement learning approach for hypergraph influence maximization with independent cascade model

Noise scheduling and out-of-distribution generalisation in deep reinforcement learning for 6-DOF robotic grasping

Abstract Exploration strategy is a fundamental but underexplored design choice in deep reinforcement learning for robotic manipulation. This paper presents a controlled empirical comparison of three off-policy configurations on a 6-DOF robotic grasping task using a Universal Robots UR5e in the RoboSuite simulation envi...

Active Visual Inspection with Deep Reinforcement Learning for Disease Diagnosis in Tomato Plants

Human-centric digital twins in industry 5.0: technologies, applications, and future directions

Industry 5.0 (I5.0) emphasizes industrial technologies that are human-centric, sustainable, and resilient. Human-Centric Digital Twins (HCDTs) support this transition by integrating worker data with robots, machines, tasks, and industrial environments. However, the relevant research remains fragmented across human mode...

Confocal images of coronal slices to verify ChR2 expression in dopaminergic midbrain

This data set contains immunostaining confirmation of ChR2 expression in dopaminergic midbrain, accompanying Bouabid, Vu, et al, 2026. "An anatomical hotspot for striatal dopamine-acetylcholine interactions during reward and movement: multi-fiber photometry data": Abstract: Dopamine (DA) and acetylcholine (ACh) are key...

Evolutionary–Neural Hybrids for Interference-Aware Channel Assignment in Ultra-Dense 6G Networks: A Survey, Taxonomy, and Research Roadmap

Ultra-dense networks (UDNs) are a defining feature of 6G: thousands of small cells and devices share a limited spectrum, so co-channel interference rather than noise limits performance. Assigning channels to cells or users in such networks is a combinatorial, NP-hard problem whose search space grows exponentially with...

Adaptive curriculum learning-based path planning and data collection for autonomous underwater vehicles under extreme sea conditions

Path planning and data collection for Autonomous Underwater Vehicles (AUVs) under extreme sea conditions face severe environmental disturbances and high task complexity, leading to low training efficiency and divergence in traditional reinforcement learning. To address the limitations of existing fixed curriculum learn...

Development and validation of VentPilot: an AI-based recommendation system for mechanical ventilation

BACKGROUND: Mechanical ventilation requires repeated adjustment to changing patient physiology, but consistent individualized management remains challenging. We developed VentPilot, an artificial intelligence-based system for recommending ventilator settings, and evaluated it in multicenter retrospective validation coh...