Purpose: Simulating markets using agent-based models must consider pricing. However, the strategic nature of prices limits the development of agent-based models with endogenous price competition.Methods: I propose an agent-based algorithm based on Game Theory that allows us to simulate the pricing in different markets. I test the algorithm in five theoretical economic models from the industrial organization literature.
Results:In all cases, the algorithm is capable of simulating the optimal pricing of those markets. It is also tested in two more cases: one in which the original work fails to predict the optimal outcome, and another one that is quite complex to solve analytically. Lastly, I present two potential extensions of this algorithm: one dynamic, and another one based on quantity competition.
Conclusions:This algorithm opens the door to the extensive inclusion of pricing in agent-based models, but also, it helps to establish a link between the industrial organization literature and the agent-based modeling.