feat(*): Add basic working script that runs an agent against itself in a Rocket League environment

rl-training.py

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+import rlgym
+from stable_baselines3.ppo import PPO
+from rlgym_tools.sb3_utils import SB3SingleInstanceEnv
+import os
+
+# set up the folders
+models_dir = "models/PPO-rl"
+logdir = "logs"
+
+if not os.path.exists(models_dir):
+    os.makedirs(models_dir)
+
+if not os.path.exists(logdir):
+    os.makedirs(logdir)
+
+# set up the RLGym environment
+gym_env = rlgym.make(use_injector=True, self_play=True)
+
+# wrap the RLGym environment with the single instance wrapper
+env = SB3SingleInstanceEnv(gym_env)
+
+# create a PPO instance and start learning
+learner = PPO(policy="MlpPolicy", env=env, verbose=1, tensorboard_log=logdir)
+
+TIMESTEPS = 10000
+iters = 0
+for i in range(1, 30):
+    learner.learn(total_timesteps=TIMESTEPS, reset_num_timesteps=False, tb_log_name="PPO-rl")
+    learner.save(f"{models_dir}/{TIMESTEPS*i}")