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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.

Contents

  • rl_knapsack_clippedppo_coach_tensorflow_customEnv.ipynb: Notebook used for training the policy to address the knapsack problem.
  • src/
    • 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.