Decision-Making Using Random Boolean Networks In The El Farol Bar Problem

In our daily lives we often face binary decisions where we seek to take either the minority or the majority side. One of these binary decision scenarios is the El Farol Bar Problem, which has been used to study how agents achieve coordination. Previous works have shown that agents may reach appropriate levels of coordination, mostly by looking at their own individual strategies that consider the complete history of the bar attendance. No structure of the network of players has been explicitly considered. Here we use the formalism of random boolean networks to help agents to make decisions considering a network of other decision-makers. This is especially useful because random boolean networks allow the mapping of actions of K other agents (hence not based on complete history) to the decision-making of each single individual. Therefore a contribution of this work is the fact that we consider agents as participants of a social network. In the original proposition for this problem, strategies would change within time and eventually would lead agents to, collectively, decide on a efficient attendance, at each time step. Hence there was no explicit modeling of such a social network. Our results using random boolean networks show a similar pattern of convergence to an efficient attendance, provided agents do experimentation with the number of boolean functions, have a good update strategy, and a certain number of neighbors is considered.