Multi-agent task allocation is a well-studied field with many proven algorithms.In real-world applications, many tasks have complicated coupled relationships that affect the feasibility of some algorithms.In this paper, we leverage on the properties of potential games and introduce a scheduling algorithm Table Top Game Accessories to provide feasible solutions in allocation scenarios with complicated spatial and temporal dependence.Additionally, we propose the use of random sampling in a Distributed Stochastic Algorithm Wooden Figure to enhance speed of convergence.
We demonstrate the feasibility of such an approach in a simulated disaster relief operation and show that feasibly good results can be obtained when the confirmation and sample size requirements are properly selected.