reinforcement learning

Invited: EDA-env: A Reinforcement Learning Environment for RTL-to-GDS Design with Independent Scoring

Artifacts accompanying the paper “Invited: EDA-env: A Reinforcement Learning Environment for RTL-to-GDS Design with Independent Scoring.” See the included README for contents and reproduction instructions.

Longévité OS : Compendium libre des biomarqueurs du vieillissement et des protocoles d'intervention open source

Abstract EN This document, produced with the assistance of ChatGPT o3 and ChatGPT 5 Thinking, is released under the Apache 2.0 licence. It is a voluntary defensive publication (prior art) and therefore enters the prior art upon release under the applicable patent statutes EPC Art. 54(2) (European Patent Convention), Fr...

Invited: EDA-env: A Reinforcement Learning Environment for RTL-to-GDS Design with Independent Scoring

Artifacts accompanying the paper “Invited: EDA-env: A Reinforcement Learning Environment for RTL-to-GDS Design with Independent Scoring.” See the included README for contents and reproduction instructions.

Monte Carlo-driven reinforcement learning for smart manufacturing systems

Developing a smart control system capable of accounting for the dynamics of industrial equipment state changes and promptly detecting features of developing failures is currently a pressing issue. The goal of this study is to develop an intelligent technology for industrial equipment state diagnostics based on a modifi...

Feuille de Route IA pour la Prévention, le Traitement et l'Éradication des Maladies Prioritaires

Abstract ENThis document, produced with the assistance of ChatGPT o3 and GPT-5 Thinking, is released under the Apache 2.0 licence. It is a voluntary defensive publication (prior art) and therefore enters the prior art upon release under the applicable patent statutes (art. L 611-11 CPI / art. 54(2) CBE), 35 U.S.C. §102...

Replication Package for "The State of RL4SE: A Task-Oriented Review of Research on Reinforcement Learning for Software Engineering"

This record contains the replication package for the survey “The State of RL4SE: A Task-Oriented Review of Research on Reinforcement Learning for Software Engineering.” The package supports the study-identification, screening, classification, and artifact-availability results reported in the survey. It contains: • cand...

Large Organismic Model: A Developmental Architecture for Embodied, Affective, and Self-Directed Artificial Intelligence

We propose the Large Organismic Model (LOM), a developmental architecture for artificial intelligence. Rather than reporting the performance of an implemented system, this position paper formulates a testable computational hypothesis that integrates ideas from biology, developmental neuroscience, 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...