Analyzing Games with a Variable Number of Players

Abstract

We introduce a novel technique that uses a multi-headed neural network to analyze symmetric games with a variable number of players, where the number of participants falls in a specified range. We hypothesize that the payoffs in a game with x players are similar or related to the same game with x + 1 players, given a large value of x. With this hypothesis, we generalize prior work to analyze games with a large, variable number of players.