Proximal policy optimization
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Proximal Policy Optimization (PPO) is a family of model-free reinforcement learning algorithms. PPO algorithms are policy gradient methods, which means that they search the space of policies rather than assigning values to state-action pairs.
PPO algorithms have some of the benefits of trust region policy optimization (TRPO) algorithms, but they are simpler to implement, more general, and have better sample complexity.[1]
See also
References
- ^ Schulman, John; Wolski, Filip; Dhariwal, Prafulla; Radford, Alec; Klimov, Oleg (2017). "Proximal Policy Optimization Algorithms". arXiv:1707.06347.