reinforcement learning

Machine Learning-Driven Strength Prediction of Intermediate Crack-Induced Debonding in FRP-Strengthened RC Beams

A Multi-Layer Learning Architecture for Optimal Power Sharing Between Electric Vehicles and Microgrids

A multi layer learning architecture is proposed for optimizing the distribution of electric vehicle power among microgrids. The architecture includes three layers: prediction, coordination, and real-time control. Using a prediction layer to forecast demand loads, available renewable energy generation rates, and vehicle...

Learning Together and Against Each Other: How Multiple Reinforcement-Learning Agents Coordinate, Compete and Where the Field is Heading

The obstacles that distinguish MARL from its singleagent counterpart are discussed, namely a moving-target learning problem, the difficulty of dividing a shared reward among team members, limited local views, and growth of the joint action space, and why training with global information but acting on local information...

Multibody dynamic modelling and guided reinforcement learning for a novel air suspension system of semi-trailers

Vehicle vibrations during long-haul logistics transportation can significantly degrade ride comfort and increase the risk of cargo damage. To address this issue, this paper proposes a novel torsion-beam air suspension configuration and a guided reinforcement learning–based semi-active control strategy. First, a multibo...

Corporate AI Training Program Template

A template for corporate AI training with role groups, learning objectives, governance practice, session design and post-training reinforcement.

Dynamic driver behavior modeling with GMM for sustainable traffic signal control in deep reinforcement learning

Adaptive traffic signal control is crucial for improving urban mobility and supporting environmental sustainability. Driver behavior heterogeneity has a significant impact on intersection performance, but its effective integration into reinforcement learning models remains challenging. This study proposes HARLight, a s...

Sub-second dopaminergic reinforcement orchestrates juvenile social play and is disrupted in Shank3 deficiency. Chen et al. (Enriched version)

This dataset accompanies a study testing whether nucleus accumbens dopamine (DA) acts as an action-contingent reinforcement signal shaping juvenile social play in a sex-divergent manner, and whether Shank3 deficiency disrupts this signal. We collected multi-modal data from wild‑type (WT) and Shank3+/- (PND 35-85) durin...

Coordination Under Pressure: How Topology Coupling, Fairness Constraints, Censored Feedback, Deliberation Failure, and Communication Efficiency Jointly Define a Candidate Design Framework for Scalable Multi-Agent Coordination

This version corrects a wrong arXiv identifier and removes the results of a withdrawn preprint. Version 2 cited the CONCAT framework as arXiv:2605.29511, which is a different paper (DynaGraph); CONCAT is arXiv:2605.29612, and all three citations are corrected. CONCAT was then withdrawn by its authors on 2026-09-22, who...

Structured Prediction Meets Neural Geometry: How Compositionality, Representational Manifolds, Criticality, and Hierarchical Coding Jointly Constrain What Neural Circuits Compute

This version (2026-09-26) corrects a citation error found by an automated check and confirmed by hand against the arXiv abstracts. Version 2 cited the identifier 2606.04428, an unrelated astrophysics paper on fast-spinning black holes, for the theoretical framework in which chaotic recurrent dynamics produce local roug...

Causal Machine Learning in the Real World

Causal inference has been studied for a long time. However, it is not always clear how current causal models can best be adapted for practical use. In particular, there remains a gap between the theoretical settings in which these models are developed and the requirements of real-world clinical practice. Furthermore, s...

Project TALOS: Tactical Agentic Literature Orchestration System

Project TALOS is an autonomous research intelligence platform powered by deep reinforcement learning (DDDQN), multi-tier LLM orchestration, and the Grey Wolf Optimizer (GWO). It conducts end-to-end scientific literature discovery and evaluation across 16 academic APIs.

A novel real-time integrated adaptive stable offloading (RIASO) algorithm in multi-access edge computing

A Real-time Integrated Adaptive Stable Offloading (RIASO) algorithm is proposed based on Lyapunov optimization (LO), Multi Output Learning (MOL), and DRL that optimizes network data processing capabilities while maintaining long-term data queue stability and average consumed power constraints that makes it adaptable to...