Use trained RL agent to predit output on random test sample

29 次查看（过去 30 天）

显示更早的评论

Praveen Verma 2024-11-19，0:37

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2167108-use-trained-rl-agent-to-predit-output-on-random-test-sample

评论： Hitesh 2024-11-19，5:52

在 MATLAB Online 中打开

This is my code

  Required_agent=load('G1_Agents.mat', 'agent1', 'agent2','agent3');
        test_sample=final_test_data_rearranged;
        final_test_sample = reshape(test_sample, [], 1);
        fprintf('Required_sample = %d\n', i)
        agent1 = Required_agent.agent1;
        agent2 = Required_agent.agent2;
        agent3 = Required_agent.agent3;
        policy1=generatePolicyFunction(agent1);
        policy2=generatePolicyFunction(agent2);
        policy3=generatePolicyFunction(agent3);
        action1 = getAction(policy1,final_test_sample);
        action2 = getAction(policy2,final_test_sample);
        action3 = getAction(policy3,final_test_sample);

When I run this code, the error is:

Incorrect number or types of inputs or outputs for function getAction.

action1 = getAction(policy1,final_test_sample);

I have cross-checked the final_test_sample; it has the same size as the input used during the training of the RL agent.

2 个评论
显示无隐藏无

Walter Roberson 2024-11-19，0:52

Note that the second input to getAction must be a cell array. We cannot tell from your code what data type final_test_sample is.

Hitesh 2024-11-19，5:52

Hi @Praveen Verma,

Could you share the complete code or the file so that we reproduce the error and can further look for root cause of the error ?

请先登录，再进行评论。

请先登录，再回答此问题。

回答（0 个）

请先登录，再回答此问题。

类别

AI and Statistics Deep Learning Toolbox Applications Autonomous and Control Systems Reinforcement Learning

在 Help Center 和 File Exchange 中查找有关 Reinforcement Learning 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Translated by