szrlee/HyperAgent

The official code repo for HyperAgent algorithm published in ICML 2024.

20
/ 100
Experimental

HyperAgent helps machine learning researchers efficiently train intelligent agents for complex environments like Atari games. It takes raw game data and outputs highly performant decision-making policies with significantly less training data and computational resources compared to existing methods. This is ideal for researchers focused on reinforcement learning and artificial intelligence.

No commits in the last 6 months.

Use this if you are a machine learning researcher or student looking to develop highly data- and computation-efficient reinforcement learning agents.

Not ideal if you are a practitioner looking for a ready-to-use, no-code AI solution for business problems, as this is a research implementation requiring programming skills.

reinforcement-learning artificial-intelligence-research agent-training atari-games deep-sea-navigation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
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Language

Python

License

MIT

Last pushed

Oct 21, 2024

Commits (30d)

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