policy
multi_agent
ajoginapally · PyTorch
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Overview
Name
multi_agent
Author
ajoginapally
Framework
PyTorch
License
unknown
Skill type
other
Evidence level
untested
Task description
Creates 2 RL agents that compete and cooperate to make market based decisions. Uses a Q-Network and Reward model for the agents, and shows all the actions of both agents using JS frontend and FASTAPI backend
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
3+17 mentioned but not in catalog yetCompatible environments
0No environments list multi_agent yet.
Datasets that reference this policy
0No datasets reference multi_agent yet.