Evolving effective coordination strategies in tightly coupled multi-agent settings with sparse
team fitness evaluations is challenging. It relies on multiple agents simultaneously stumbling …

Learning in tightly coupled multiagent settings with sparse rewards is challenging because
multiple agents must reach the goal state simultaneously for the team to receive a reward …

The purpose of this paper is to present concepts of a paradigm to understand, model,
simulate and design a type of coordination among systems. The paradigm is called …