policy
Table-Tennis-Agent
Manikantacb · PyTorch
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Overview
Name
Table-Tennis-Agent
Author
Manikantacb
Framework
PyTorch
License
unknown
Skill type
manipulation
Evidence level
untested
Task description
The objective of our project is to understand how we can use machine learning algorithms to train dual AI agents to play a game of table tennis. Through this process we develop both dual-agent and single-agent game, exploring different RL models. Our efforts delivers very capable table-tennis agents
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
2+18 mentioned but not in catalog yetCompatible environments
0No environments list Table-Tennis-Agent yet.
Datasets that reference this policy
0No datasets reference Table-Tennis-Agent yet.