Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence

Neural Information Processing Systems 

Multi-agent AI research promises a path to develop human-like and humancompatible intelligent technologies that complement the solipsistic view of other approaches, which mostly do not consider interactions between agents. Aiming to make progress in this direction, the Melting Pot contest 2023 focused on the problem of cooperation among interacting agents and challenged researchers to push the boundaries of multi-agent reinforcement learning (MARL) for mixed-motive games. The contest leveraged the Melting Pot environment suite to rigorously evaluate how well agents can adapt their cooperative skills to interact with novel partners in unforeseen situations [1, 2]. Unlike other reinforcement learning challenges, this challenge focused on social rather than environmental generalization.