Use trained RL agent to predit output on random test sample

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.

[Walter Roberson]

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]

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 ?