Research Scientist @ Convergence. Ex-Huawei, NVIDIA.

PhD in Multi-Agent Reinforcement Learning at the University of Edinburgh and the Autonomous Agents Research Group.

Co-author of Multi-Agent Reinforcement Learning: Foundations and Modern Approaches.

Contact Me :: [email protected] exact spelling as above

Note 1: I have lost access to my old @ed.ac.uk email address (a relic from my days at the University of Edinburgh). If you’re trying to reach me and found that address in one of my papers, don’t worry—-I’m still here and reachable!

Note 2: I prefer to correspond in English whenever possible. Emails not written in English might not get the attention they deserve!

My public GPG key to check my e-signature or send me encrypted e-mails.

Multi-Agent Reinforcement Learning

The first comprehensive introduction to the field of multi-agent reinforcement learning, an area of machine learning in which multiple decision-making agents learn to optimally interact in a shared environment.

Learn more in the official website: www.marl-book.com

Physical Copy: MARL MIT Press

GitHub projects

Here are some of my GitHub projects that might interest you:

• Level-Based Foraging: A Python implementation of the Level-Based Foraging environment, widely used for benchmarking multi-agent reinforcement learning algorithms.
• Multi-Robot Warehouse: A customizable environment for studying coordination and collaboration in multi-agent settings, inspired by real-world warehouse scenarios.
• EPyMARL: A streamlined library for multi-agent reinforcement learning, offering implementations of popular MARL algorithms with an emphasis on scalability and ease of use.