reinforcement learning

Power-fade-aware deep reinforcement learning for second-life battery energy management

saberrrostami/cmfg-rl-reconfiguration-reproducibility: Reproducibility package v1.0.1

Reproducibility package accompanying the manuscript "Dynamic service composition reconfiguration in cloud manufacturing under limited shared recovery capacity: A reinforcement learning approach".

Reproducibility archive for Target-Scale Sensitivity in Adaptive Pessimism for Tabular Offline Reinforcement Learning: An EdNet-KT4 Study

This archive accompanies the manuscript "Target-Scale Sensitivity in Adaptive Pessimism for Tabular Offline Reinforcement Learning: An EdNet-KT4 Study." It contains the analysis code, frozen experimental protocol, primary clean-200k results, and sensitivity-analysis results needed to reproduce the reported tables and f...

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.

Is Physics Actually Derived From Path Availability? What if What Causes Physics is Merely the Recursion of Possibilities?

Physics, as we have inherited it, is a set of magnificent local dialects speaking past each other. Fermat tells us how light navigates. Hamilton tells us how matter navigates. Boltzmann tells us how heat navigates. Schrödinger tells us how amplitudes navigate. Einstein tells us how geometry navigates. None of these dia...

Reproducibility archive for Target-Scale Sensitivity in Adaptive Pessimism for Tabular Offline Reinforcement Learning: An EdNet-KT4 Study

This archive accompanies the manuscript "Target-Scale Sensitivity in Adaptive Pessimism for Tabular Offline Reinforcement Learning: An EdNet-KT4 Study." It contains the analysis code, frozen experimental protocol, primary clean-200k results, and sensitivity-analysis results needed to reproduce the reported tables and f...

Adaptive Terrain Traversal: A Model-Free Reinforcement Learning Approach to Lunar Rover Active Suspension System

Velocity adaptive preview path tracking control for autonomous vehicles using deep reinforcement learning with Lyapunov function-based reward shaping

Traditional rule-based path tracking controllers of autonomous vehicles (AVs) often struggle with nonlinear vehicle dynamics, parameter tuning, and changes in road conditions. Learning-based methods partly address these issues, but remain limited in adapting to velocity changes, exploiting the preview information from...

Deep Q-Network-Assisted Energy-Aware Scheduling Framework (DQN-EAS) for Scientific Workflows

In modern computing environments, scientific workflows play a vital role in orchestrating complex computational tasks across diverse resources and domains. As high-performance computing (HPC) systems continue to evolve, the need for energy-efficient scheduling methods — without compromising task completion time — has b...

Artificial Intelligence in CPU and ASIC Design: Applications, Design-Space Exploration, and Engineering Constraints

Modern CPU and application-specific integrated circuit (ASIC) development requires engineers to search large design spaces while satisfying power, performance, area, timing, and correctness constraints. Artificial intelligence (AI) is increasingly being integrated into electronic design automation (EDA) to accelerate p...

Cache-Fused Kinematic Rails: Ex-Ante Silicon Alignment via In-Vivo KV-Cache Metric Grafting

Abstract of Cache-Fused Kinematic Rails: Ex-Ante Silicon Alignment via In-Vivo KV-Cache Metric Grafting Current Large Language Model (LLM) alignment relies primarily on post-hoc, output-level correction mechanisms such as external API meta-governors, Reinforcement Learning from Human Feedback (RLHF), or post-generation...

Artificial Intelligence in CPU and ASIC Design: Applications, Design-Space Exploration, and Engineering Constraints

Modern CPU and application-specific integrated circuit (ASIC) development requires engineers to search large design spaces while satisfying power, performance, area, timing, and correctness constraints. Artificial intelligence (AI) is increasingly being integrated into electronic design automation (EDA) to accelerate p...