Key question: can multi-agent optimization problems help reinforcement learning stuff
using deep RL for combinatorial optimiazation
- fast inference scals well with instance size
- maybe difficult to actually discover optimal solution: high sample complexity, or failing to find good solutions
- doesn’t generalize well
why multi-agent works
- decentralized training to improve sample efficiency
- adversarial training