The rapidly growing field of computational social choice, at the intersection of computer science and economics, deals with the computational aspects of collective decision making. This handbook, written by thirty-six prominent members of the computational social choice community, covers the field comprehensively. Chapters devoted to each of the field's major themes offer detailed introductions. Topics include voting theory (such as the computational complexity of winner determination and ...

A balanced and thought-provoking guide to all the big questions about AI and ethicsCan computers understand morality? Can they respect privacy? And what can we do to make AI safe and fair?The artificial intelligence revolution has begun. Today, there are self-driving cars on our streets, autonomous weapons in our armies, robot surgeons in our hospitals – and AI's presence in our lives will only increase. Some see t...

**Brought to you by Penguin.A reassuring and thought-provoking guide to all the big questions about AI and ethics**Should robots ever be considered free? Will computers transcend human intelligence? And what can we do to make sure AI is safe?The artificial intelligence revolution has begun. Today, there are self-driving cars on our streets, autonomous weapons in our armies, robot surgeons in our hospitals - and AI's presence in our lives will only increase....

Kenneth J. Arrow's pathbreaking "impossibility theorem" was a watershed innovation in the history of welfare economics, voting theory, and collective choice, demonstrating that there is no voting rule that satisfies the four desirable axioms of decisiveness, consensus, nondictatorship, and independence.In this book Eric Maskin and Amartya Sen explore the implications of Arrow's theorem. Sen considers its ongoing utility, exploring the theorem's value and limitations in relation to ...

Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computatio...

Most theories of elections assume that voters and political actors are fully rational. While these formulations produce many insights, they also generate anomalies--most famously, about turnout. The rise of behavioral economics has posed new challenges to the premise of rationality. This groundbreaking book provides a behavioral theory of elections based on the notion that all actors--politicians as well as voters--are only boundedly rational. The theory posits learning via trial and error...

Multiagent systems combine multiple autonomous entities, each having diverging interests or different information. This overview of the field offers a computer science perspective, but also draws on ideas from game theory, economics, operations research, logic, philosophy and linguistics. It will serve as a reference for researchers in each of these fields, and be used as a text for advanced undergraduate or graduate courses. The authors emphasize foundations to create a broad and rigorous...

This collection illustrates how nonlinear methods can provide new insight into existing political questions. Politics is often characterized by unexpected consequences, sensitivity to small changes, non-equilibrium dynamics, the emergence of patterns, and sudden changes in outcomes. These are all attributes of nonlinear processes. Bringing together a variety of recent nonlinear modeling approaches, Political Complexity explores what happens when political actors operate in a dynam...

This unique book is the first comprehensive guide to the discovery, analysis, and evaluation of natural experiments - an increasingly popular methodology in the social sciences. Thad Dunning provides an introduction to key issues in causal inference, including model specification, and emphasizes the importance of strong research design over complex statistical analysis. Surveying many examples of standard natural experiments, regression-discontinuity designs, and instrumental-variables des...

Qualitative Comparative Analysis (QCA) and other set-theoretic methods distinguish themselves from other approaches to the study of social phenomena by using sets and the search for set relations. In virtually all social science fields, statements about social phenomena can be framed in terms of set relations, and using set-theoretic methods to investigate these statements is therefore highly valuable. This book guides readers through the basic principles of set theory and then on to the a...

Party competition for votes in free and fair elections involves complex interactions by multiple actors in political landscapes that are continuously evolving, yet classical theoretical approaches to the subject leave many important questions unanswered. Here Michael Laver and Ernest Sergenti offer the first comprehensive treatment of party competition using the computational techniques of agent-based modeling. This exciting new technology enables researchers to model competition between s...

This book provides a solution to the ecological inference problem, which has plagued users of statistical methods for over seventy-five years: How can researchers reliably infer individual-level behavior from aggregate (ecological) data? In political science, this question arises when individual-level surveys are unavailable (for instance, local or comparative electoral politics), unreliable (racial politics), insufficient (political geography), or infeasible (political history). This ecol...