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Proximal policy optimization

Technique

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About Proximal policy optimization · from Wikipedia

Proximal policy optimization (PPO) is a reinforcement learning (RL) algorithm for training an intelligent agent. Specifically, it is a policy gradient method, often used for deep RL when the policy network is very large.

Summary from Wikipedia ↗, CC BY-SA 4.0.
  • Deep reinforcement learning May 2025
    The notebook trains an agent to land a spacecraft in the LunarLander environment from Gymnasium, using the PPO algorithm from Stable-Baselines3.

As data

Everything on this page is read from triples in the knowledge graph. These are the 4 it states about Proximal policy optimization, and 1 more its ontology implies; the console runs SPARQL over the whole graph, here in your browser.

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id:PPO
    a cj:Technique ;
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Works 1
Deep reinforcement learning