LGROSep 15, 2017

Shapechanger: Environments for Transfer Learning

arXiv:1709.05070v1Has Code
Originality Synthesis-oriented
AI Analysis

This provides a tool for researchers and practitioners in robotics to facilitate transfer learning, but it is incremental as it builds on existing transfer learning concepts.

The authors introduced Shapechanger, a library for transfer reinforcement learning in robotic tasks, addressing knowledge transfer across simulation and real environments with continuous states and actions, and it is open-sourced for ongoing development.

We present Shapechanger, a library for transfer reinforcement learning specifically designed for robotic tasks. We consider three types of knowledge transfer---from simulation to simulation, from simulation to real, and from real to real---and a wide range of tasks with continuous states and actions. Shapechanger is under active development and open-sourced at: https://github.com/seba-1511/shapechanger/.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes