A game-theoretical method for dynamic agent-zone allocation problems (2020)
We consider an agent-zone allocation problem, where agents are expected to optimally allocate themselves into a set of zones. For such, we use a game-theoretical formulation of the problem, where the agents make individual decisions to optimize their own utility function, while they also optimize the global utility. We use a negotiation mechanism named generalized regret monitoring with fading memory and inertia, which helps to obtain an optimal solution. Moreover, we propose a utility function based on carrying capacities, so that the agents consider the occupation of each zone while making their decisions. We present a sensitivity analysis of the parameters used in the negotiation mechanism and the utility function. Finally, we show some simulation results of three scenarios and their corresponding statistical analysis.