Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions Asish Ghoshal Jean Honorio
[email protected] [email protected] Department of Computer Science, Purdue University, West Lafayette, IN, U.S.A. - 47907. Abstract identified, from congressional voting records, the most influential senators in the U.S. congress — a small In this paper we obtain sufficient and neces- set of senators whose collective behavior forces every sary conditions on the number of samples re- other senator to a unique choice of vote. Irfan and quired for exact recovery of the pure-strategy Ortiz [4] also observed that the most influential sena- Nash equilibria (PSNE) set of a graphical tors were strikingly similar to the gang-of-six senators, game from noisy observations of joint actions. formed during the national debt ceiling negotiations of We consider sparse linear influence games — 2011. Further, using graphical games, Honorio and Or- a parametric class of graphical games with tiz [6] showed that Obama’s influence on Republicans linear payoffs, and represented by directed increased in the last sessions before candidacy, while graphs of n nodes (players) and in-degree of McCain’s influence on Republicans decreased. at most k.Weshowthatonecanefficiently The problems in algorithmic game theory described recover the PSNE set of a linear influence above, i.e., computing the Nash equilibria, comput- game with k2 log n samples, under very O ing the price of anarchy or finding the most influ- general observation models. On the other ential agents, require a known graphical game which hand, we show that ⌦(k log n) samples are is not available apriori in real-world settings.