"Given the complexity of social processes, many social scientists question the assumption of rationality underlying game theoretic models of elections. The natural solution, to assume bounded rationality, has been stifled by the abundance of possible alternative models. This wonderful book examines a class of models grounded in aspiration-based learning and shows how they produce deep, explanatory insights into voter choice, turnout, party competition, and electoral outcomes. A tour de force!"--Scott E. Page, author of "The Difference" and "Diversity and Complexity""Distinctive in its use of aspiration-based adjustment models as a replacement for the traditional rational choice approaches, this book is clearly the first to develop a coherent model of elections based on reinforcement learning. Clearly written and effectively presented, it will advance the debate on the use of both behavioral and rational choice models in political science."--Mark Fey, University of Rochester