Questions tagged [proximal-policy-optimization]

For questions related to the reinforcement learning algorithm called proximal policy optimization (PPO), which was introduced in the paper "Proximal Policy Optimization Algorithms" (2017) by John Schulman et al.

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Reinforcement learning with PPO: rewards decreasing

I'm trying to train a PPO agent and my average rewards graph looks like this. Could this indicate that it's stuck at a local maximum? Do I need to promote exploring by increasing the entropy or does ...
4
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2answers
341 views

How is parallelism implemented in RL algorithms like PPO?

There are multiple ways to implement parallelism in reinforcement learning. One is to use parallel workers running in their own environments to collect data in parallel, instead of using replay memory ...
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1answer
68 views

Why don't we decorrelate transitions for policy-based data?

I'm implementing PPO myself strictly follow the steps: sample transitions randomly shuffle the sampled transitions compute gradients and update networks using the sampled transitions drop transitions ...
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1answer
922 views

Getting NaN from A3C PPO model [closed]

I've pieced together this A3C w/ PPO Gym Pendulum example, but I'm finding after a while, when attempting to get the action from the model, I get a NaN return: ...
2
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1answer
664 views

How do I calculate the policy in the Proximal Policy Optimization algorithm?

I recently watched the video on Proximal Policy Optimization (PPO). Now, I want to upgrade my actor-critic algorithm written in PyTorch with PPO, but I'am not sure how the new parameters / thetas are ...
14
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3answers
5k views

How to implement a variable action space in Proximal Policy Optimization?

I'm coding a Proximal Policy Optimization (PPO) agent with the Tensorforce library (which is built on top of TensorFlow). The first environment was very simple. Now, I'm diving into a more complex ...
6
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2answers
972 views

Why is the log probability replaced with the importance sampling in the loss function?

In the Trust-Region Policy Optimisation (TRPO) algorithm (and subsequently in PPO also), I do not understand the motivation behind replacing the log probability term from standard policy gradients $$L^...
4
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1answer
271 views

Understanding multi-iteration updates of the model in the Proximal Policy Optimization algorithm

I have a general question about the updating of the network/model in the PPO algorithm. If I understand it correctly, there are multiple iterations of weight updates done on the model with data that ...
14
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1answer
7k views

How can policy gradients be applied in the case of multiple continuous actions?

Trusted Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO) are two cutting edge policy gradients algorithms. When using a single continuous action, normally, you would use some ...

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