Unanswered questions ahead

1 minute read

Published: July 15, 2025

Challenges Ahead

1. Many optimization problem suffers from curse of dimension. In the inverse case of multi-agent systems, the joint decision space can get crazily large when we have too many agents or high dimension dynamics, thus becoming computationally prohibitive. How can we effectively compress the state space, without sacrificing too much of the objective/constraints inference quality?