Comprehensive agent benchmarking Tools for Every Need

Get access to agent benchmarking solutions that address multiple requirements. One-stop resources for streamlined workflows.

agent benchmarking

  • A Python OpenAI Gym environment simulating the Beer Game supply chain for training and evaluating RL agents.
    0
    0
    What is Beer Game Environment?
    The Beer Game Environment provides a discrete-time simulation of a four-stage beer supply chain—retailer, wholesaler, distributor, and manufacturer—exposing an OpenAI Gym interface. Agents receive observations including on-hand inventory, pipeline stock, and incoming orders, then output order quantities. The environment computes per-step costs for inventory holding and backorders, and supports customizable demand distributions and lead times. It integrates seamlessly with popular RL libraries like Stable Baselines3, enabling researchers and educators to benchmark and train algorithms on supply chain optimization tasks.
Featured