Introduction to the AI Magazine Special Issue on Algorithmic Game Theory

We briefly survey the rise of game theory as a topic of study in artificial intelligence, and explain the term algorithmic game theory. We then describe three broad areas of current inquiry by AI researchers in algorithmic game theory: game playing, social choice, and mechanism design. Finally, we give short summaries of each of the six articles appearing in this issue. 1 Algorithmic Game Theory and Artificial Intelligence Game theory is a branch of mathematics devoted to studying interaction among rational and self-interested agents. The field took on its modern form in the 1940s and 1950s (von Neumann and Morgenstern, 1947; Nash, 1950; Kuhn, 1953), with even earlier antecedents (e.g., Zermelo, 1913; von Neumann, 1928). Although it has had occasional and significant overlap with computer science over the years, game theory received most of its early study by economists. Indeed, game theory now serves as perhaps the main analytical framework in microeconomic theory, as evidenced by its prominent role in economics textbooks (e.g., Mas-Colell et al., 1995) and by the many Nobel prizes awarded to prominent game theorists. Artificial intelligence got its start shortly after game theory (McCarthy et al., 1955), and indeed pioneers such as von Neumann and Simon made early contributions to both fields (see, e.g., Findler, 1988; Simon, 1981). Both game theory and AI draw (non-exclusively) on decision theory (von Neumann and Morgenstern, 1947); e.g., one prominent view defines artificial intelligence as “the study and construction of rational agents” (Russell and Norvig, 2003), and hence takes a decision-theoretic approach when the world is stochastic. However, artificial intelligence spent most of its first forty years focused on the design and analysis of agents that act in isolation, and hence had little need for game-theoretic analysis. Starting in the mid to late 1990s, game theory became a major topic of study for computer scientists, for at least two main reasons. First, economists began to be interested in systems whose computational properties posed serious ∗Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore †Department of Computer Science, University of British Columbia, Canada