Connor202020/Reinforce-CartPole-v1

Reinforce Agent playing CartPole-v1

This is a trained model of a Reinforce agent playing CartPole-v1 . To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction

to train a great model, you need to modify the hyperparameters

cartpole_hyperparameters = {
    "h_size": 64,  
    "n_training_episodes": 2000,  
    "n_evaluation_episodes": 20,  
    "max_t": 1000, 
    "gamma": 0.99,  
    "lr": 1e-3, 
    "env_id": env_id,
    "state_space": s_size,
    "action_space": a_size,
}

Score Record:

Episode 100	    Average Score: 29.39
Episode 200   	Average Score: 40.43
Episode 300    	Average Score: 62.50
Episode 400	    Average Score: 140.69
Episode 500	    Average Score: 257.97
Episode 600	    Average Score: 385.96
Episode 700	    Average Score: 444.55
Episode 800	    Average Score: 471.07
Episode 900	    Average Score: 425.36
Episode 1000	Average Score: 469.43
Episode 1100	Average Score: 482.73
Episode 1200	Average Score: 479.17
Episode 1300	Average Score: 492.68
Episode 1400	Average Score: 487.52
Episode 1500	Average Score: 485.91
Episode 1600	Average Score: 487.56
Episode 1700	Average Score: 485.40
Episode 1800	Average Score: 494.59
Episode 1900	Average Score: 488.71
Episode 2000	Average Score: 493.33
Episode 2100	Average Score: 496.70
Episode 2200	Average Score: 498.07
Episode 2300	Average Score: 498.38
Episode 2400	Average Score: 476.29
Episode 2500	Average Score: 485.02
Episode 2600	Average Score: 481.23
Episode 2700	Average Score: 498.21
Episode 2800	Average Score: 500.00
Episode 2900	Average Score: 496.20
Episode 3000	Average Score: 494.15