by Zainul Abideen | Jul 10, 2025
Introduction to EnvPool EnvPool is a powerful open-source library designed to optimize the performance of reinforcement learning (RL) environments. By providing high-throughput environment pooling, EnvPool significantly enhances the efficiency of training RL agents,...
by Zainul Abideen | Jul 10, 2025
Introduction to Mava Mava is an advanced framework designed for multi-agent reinforcement learning (MARL). Developed by the research team at InstaDeep, Mava introduces the Sable algorithm, which treats MARL as a sequence modeling problem. This innovative approach...
by Zainul Abideen | Jul 10, 2025
Introduction to RL Games RL Games is a cutting-edge reinforcement learning (RL) library that provides high-performance capabilities for training AI agents in various environments. Built on Pytorch, this library supports advanced features such as multi-agent training,...
by Zainul Abideen | Jul 10, 2025
Introduction to Acme’s MPO The Acme project by DeepMind provides a robust implementation of Maximum a posteriori Policy Optimization (MPO), a cutting-edge approach in the field of reinforcement learning. This implementation is designed to facilitate the...
by Zainul Abideen | Jul 10, 2025
Introduction to Dopamine Dopamine is an open-source framework developed by Google for building and evaluating reinforcement learning algorithms. It is designed to facilitate research in deep reinforcement learning, particularly focusing on the implementation of...
