title: PettingZoo: Gym for Multi-Agent Reinforcement Learning
abstract: OpenAI's Gym library  contains a large, diverse set of environments that are useful benchmarks in reinforcement learning, under a single elegant Python API (with tools to develop new compliant environments) . The introduction of this library has proven a watershed moment for the reinforcement learning community, because it created an accessible set of benchmark environments that everyone could use (including wrapper important existing libraries), and because a standardized API let RL learning methods and environments from anywhere be trivially exchanged. This paper similarly introduces PettingZoo, a library of diverse set of multi-agent environments under a single elegant Python API, with tools to easily make new compliant environments.
authors: J K Terry Benjamin Black Mario Jayakumar Ananth Hari Luis Santos Clemens Dieffendahl Niall L Williams Yashas Lokesh Ryan Sullivan Caroline Horsch Praveen Ravi
hIndex: J K Terry 6