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hci gibo · Data-Science-in-Mechanical-Engineering

Research code for simulation-aided policy tuning in black-box robot learning.

bayesian-optimizationrobot-learning
Publisher repository ↗
hci gibo · Data-Science-in-Mechanical-Engineering resource page screenshot
Resource screenshot · captured 2026-10-08 · visually reviewed

Overview

Research code for simulation-aided policy tuning in black-box robot learning.

Publisher summary: “Code to reproduce the results from the paper "Simulation-Aided Policy Tuning for Black-Box Robot Learning".”

Use its repository to inspect the implementation, documentation and supported workflows. This directory record identifies the maintainer, code license and related resources; it does not claim that the project has been installed or tested on your robot.

Project information

Maintainer
Data-Science-in-Mechanical-Engineering
Primary language
Python
Repository code license
Not specified
Model-weight license
Not recorded
Dataset license
Not recorded
Hardware design license
Not recorded
Maintenance
Not archived in the last recorded metadata
Last observed repository push
2025-04-08

Code licenses do not automatically cover model weights, datasets or hardware designs. Unrecorded license details require confirmation with the publisher.

Documentation sections

  • High-Confidence Improvement Bayesian Optimization
  • Abstract
  • Cite
  • Code of the repo
  • Installation
  • Usage

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