decaying clip factor or entropy loss weight for PPO

Question

Sourabh 2024-1-9

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2068071-decaying-clip-factor-or-entropy-loss-weight-for-ppo

评论： Sourabh 2024-1-29

采纳的回答： Emmanouil Tzorakoleftherakis

Is there a way to implement decaying clip factor or entropy loss weight in PPO matlab??

or how can i reduce the exploration after certain episodes in PPO ??

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Emmanouil Tzorakoleftherakis 2024-1-24

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2068071-decaying-clip-factor-or-entropy-loss-weight-for-ppo#answer_1396746

These parameters are fixed and cannot be changed after training begins. One workaround would be to train the agent for a certain number of episodes, stop training and adjust any parameters you would like, and then continue training from where you left off.

3 个评论
显示 1更早的评论隐藏 1更早的评论

Emmanouil Tzorakoleftherakis 2024-1-29

在 MATLAB Online 中打开

Are you getting any errors? It's likely that the change is happening but it's not displayed. Can you try

format long

Sourabh 2024-1-29

yeah my mistake

its working properly and on using "format long" i can see the changes properly.

Thanks :)

请先登录，再进行评论。

Answer 2

UDAYA PEDDIRAJU 2024-1-15

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2068071-decaying-clip-factor-or-entropy-loss-weight-for-ppo#answer_1389746

在 MATLAB Online 中打开

Hi Sourabh,

For implementing decaying clip factor or entropy loss weight in PPO using MATLAB. I would suggest you use the “rlPPOAgentOptions” function in MATLAB. This function provides you with the option to set the “ClipFactor” and “EntropyLossWeight” parameters for the PPO agent. The “ClipFactor” parameter is used to specify the clip factor, which is set to 0.2 by default. The “EntropyLossWeight” parameter is used to specify the weight of the entropy loss term in the loss function. You can set these parameters to your desired values using the “rlPPOAgentOptions” function.

%a conceptual example of how you might adjust the `cliprange` value over time:
initial_cliprange = 0.2;
final_cliprange = 0.1;
total_episodes = 1000;
decay_rate = (initial_cliprange - final_cliprange) / total_episodes;
for episode = 1:total_episodes
    current_cliprange = max(final_cliprange, initial_cliprange - decay_rate * episode);
    % Update your PPO algorithm's cliprange parameter
end

Regarding your second question, you can reduce exploration after certain episodes in PPO by using the “rlTrainingOptions” function in MATLAB. This function provides you with the option to set the “ExplorationFraction” parameter, which is used to specify the fraction of the total training steps that are used for exploration. You can set this parameter to a lower value to reduce exploration after certain episodes.

For more details you can refer: https://www.mathworks.com/help/reinforcement-learning/ref/rl.option.rlppoagentoptions.html and https://www.mathworks.com/help/reinforcement-learning/ug/ppo-agents.html