Modeling the Dynamics of Collective Behavior in a Reflexive Game with an Arbitrary Number of Leaders

Abstract

An oligopoly with an arbitrary number of Stackelberg leaders under incomplete, asymmetrical agents' awareness and inadequacy of their predictions of competitors' actions is considered. Models of individual decision-making processes by agents are studied. The reflexive games theory and collective behavior theory are the theoretical basis for construction and analytical study process models. They complement each other in that reflexive games allow using the collective behavior procedures and the results of agents' reflections, leading to a Nash equilibrium. The dynamic decision-making process considered repeated static games on a range of agents' feasible responses to the expected actions of the environment, considering current economic restrictions and competitiveness in each game. Each reflexive agent in each game calculates its current goal position and changes its state, taking steps towards the current position of the goal to obtain positive profit or minimize losses. Sufficient conditions for the convergence of processes in discrete time for the case of linear costs of agents and linear demand is the main result of this work. New analytical expressions for the agents' current steps' ranges guarantee the convergence of the collective behavior models to static Nash equilibrium is obtained. That allows each agent to maximize their profit, assuming common knowledge among the agents. The processes when the agent chooses their best response are also analyzed. The latter may not give converging trajectories. The case of the duopoly in comparison with modern results is discussed in detail. Necessary mathematical lemmas, statements, and their proofs are presented.