Solving Knapsack problem with Amazon SageMaker RL
This shows an example of how to use SageMaker RL to address a canonical operations research problem. We choose which items to put in the Knapsack. Our objective is to maximize the value of the items in the bag; but we cannot put all the items in as the bag capacity is limited.
rl_knapsack_clippedppo_coach_tensorflow_customEnv.ipynb: Notebook used for training the policy to address the knapsack problem.
knapsack_env.py: custom environments and simulator defined here.
train-coach.py: launcher for coach training.
evaluate-coach.py: launcher for coach evaluation.
preset-knapsack-clippedppo.py: coach preset for Clipped PPO.