reinforcement learning

Supplemental Materials for "Uncertainty-aware Construction Task Scheduling for Human-robot Collaboration via Fuzzy-time Model and Deep Reinforcement Learning"

This record contains supplemental materials associated with the manuscript entitled “Uncertainty-aware Construction Task Scheduling for Human-robot Collaboration via Fuzzy-time Model and Deep Reinforcement Learning.” The supplemental materials provide extended figures and experimental results supporting the analyses pr...

OPTICAT: A Deep Reinforcement Learning Framework for Instance-Specific Algorithm Configuration

Optimization algorithms contain parameters that greatly influence their behavior. Finding the right settings for parameters through automated algorithm configuration has become a critical component of designing competitive algorithms. While traditional offline configurators tackle this problem by finding one configurat...

THE ROLE OF ARTIFICIAL INTELLIGENCE IN DIABETES CARE AND MANAGEMENT: A COMPREHENSIVE REVIEW

Diabetes mellitus represents a global metabolic crisis characterized by complex self-management requirements, marked physiological variability, and significant risks of microvascular and macrovascular complications. The integration of Artificial Intelligence (AI)—including Machine Learning (ML), Deep Learning (DL), Nat...

Adaptive bus bridging strategies for disrupted light rail transit networks via a two-stage reinforcement learning driven approach

Verified Deep Learning with Lean 4

A formal verification of the math of modern deep learning, written as a Lean 4 blueprint project and shipped as the code it proves. Mathlib's fderiv is the foundation; every layer's backward is derived as a vector-Jacobian product rather than asserted -- dense, ReLU, softmax cross-entropy, 2D convolution, max-pool, Bat...

Reproducibility package for "Formulation-holdout validation for reliable machine learning in replicated materials experiments: an AA6061 composite case study"

This record contains the complete reproducibility package supporting the manuscript "Formulation-holdout validation for reliable machine learning in replicated materials experiments: an AA6061 composite case study." The study evaluates 12 independently prepared AA6061 hybrid-composite specimens nested within four reinf...

Strategi Guru Tahfiz dalam Memotivasi Siswa Menghafal al-Qur’an di SMPN 6 Gunung Talang Kabupaten Solok

Tahfiz teachers’ strategies for motivating students to memorize the Qur’an are important for sustaining school tahfiz programs. However, studies specifically describing these strategies in the context of public junior high schools remain limited. This study aimed to analyze the strategies used by tahfiz teachers to mot...

Reproducibility package for "Formulation-holdout validation for reliable machine learning in replicated materials experiments: an AA6061 composite case study"

This record contains the complete reproducibility package supporting the manuscript "Formulation-holdout validation for reliable machine learning in replicated materials experiments: an AA6061 composite case study." The study evaluates 12 independently prepared AA6061 hybrid-composite specimens nested within four reinf...

Trajectory Tracking Control for UUVs Based on Deep Reinforcement Learning

The DDPG-DLPID, an adaptive motion controller, including a Deep Deterministic Policy Gradient (DDPG) reinforcement learning that can acquire the parameters of PID controllers is introduced, which achieves faster response and higher tracking accuracy, while substantially reducing tracking errors under interference condi...

Decoupling engine operation from transient loads: a Mamba-based predictive reinforcement learning framework for quasi-steady energy management in gasoline compression ignition hybrid powertrains

Physics-informed reinforcement learning for inverse design of Airy-beam metasurfaces

Artificial intelligence-driven optimization and reinforcement learning for intelligent mobile robot operations in warehouse automation: A review