Project-based subject in which students from multiple disciplines are encouraged to develop and investigate systems and ideas from their fields of study as they explore the process of building and testing models and simulations. Explores various modeling software packages, criteria for developing the most appropriate simulation for a given situation, and methods for evaluating the success and utility of models. Students with an education focus consider what and how people learn from simulations, and how modeling tools can be implemented in public school settings. Graduate students are expected to complete additional assignments. During the past ten years, simulation modeling, especially as it helps people to understand complex systems, has become a mainstream use of computational technology. The widespread popularity of "edutainment" software like SimCity and Civilization gives a clear indication of the extent to which simulation games have permeated popular culture. As these and other games have found places in the classroom, researchers have tried to ascertain what and how students learn from these environments, and what implications this has for software and curriculum design. While it can be useful to experiment with pre-built models like SimCity, a deeper understanding can come through building and manipulating models whose underlying structure is accessible. Just as a young child learns more by building a bridge out of blocks instead of merely playing with a pre-fabricated bridge, designing and creating your own models provide richer learning experiences than simply playing with pre-built models. This learning process is critically important in domains that require an understanding of complex systems, from economics and mathematics to physics and biology. In this project-based course, students from all disciplines are encouraged to understand how we learn from computer environments, develop and investigate systems and ideas from their fields of study, and delve into the process of building and testing models and simulations. In the first part of the course we will explore the design and use of games and simulations in the classroom, and the research and development issues associated with this software. We will then explore various modeling and simulation software packages, criteria for developing the most appropriate simulation for a given situation, and methods for evaluating the success and utility of models. We will also study what and how people learn from simulations (including field testing of software), and how modeling and simulation tools can be implemented in educational settings. All levels of computer experience welcome. Graduate students are expected to complete additional assignments.

Foundations and philosophical applications of Bayesian decision theory, game theory and theory of collective choice. Why should degrees of belief be probabilities? Is it always rational to maximize expected utility? If so, why and what is its utility? What is a solution to a game? What does a game-theoretic solution concept such as Nash equilibrium say about how rational players will, or should, act in a game? How are the values and the actions of groups, institutions and societies related to the values and actions of the individuals that constitute them?

Examines the long term effects of information technology on business strategy in the real estate and construction industry. Considerations include: supply chain, allocation of risk, impact on contract obligations and security, trends toward consolidation, and the convergence of information transparency and personal effectiveness. Resources are drawn from the world of dot.com entrepreneurship and "old economy" responses. Taught by case study method and grading is based on class participation and papers.

Analysis of strategic behavior in multi-person economic settings. Introduction to Nash equilibrium and its refinements: subgame-perfect equilibrium and sequential equilibrium. Applications drawn from labor economics, the economics of organization, industrial organization, international trade, and macroeconomics.

Analysis of strategic behavior in multi-person economic settings. Introduction to Nash equilibrium and its refinements: subgame-perfect equilibrium and sequential equilibrium. Applications drawn from labor economics, the economics of organization, industrial organization, international trade, and macroeconomics. Game Theory is a misnomer for Multiperson Decision Theory, the analysis of situations in which payoffs to agents depend on the behavior of other agents. It involves the analysis of conflict, cooperation, and (tacit) communication. Game theory has applications in several fields, such as economics, politics, law, biology, and computer science. In this course, I will introduce the basic tools of game theoretic analysis. In the process, I will outline some of the many applications of game theory, primarily in economics and political science. Game Theory has emerged as a branch of mathematics and is still quite mathematical. Our emphasis will be on the conceptual analysis, keeping the level of math to a minimum, especially at a level that should be quite acceptable to the average MIT student. Yet bear in mind that this still implies that you should be at ease with basic probability theory and calculus, and more importantly, you should be used to thinking in mathematical terms. Intermediate Microeconomics is also a prerequisite (simultaneous attendance to one of the intermediate courses is also acceptable). In any case, if you are taking this course, you should be prepared to work hard.

Integrates psychological insights into economic models of behavior. Discusses the limitations of standard economic models and surveys the ways in which psychological experiments have been used to learn about preferences, cognition, and behavior. Topics include trust, vengence, fairness, impatience, impulsivity, bounded rationality, learning, reinforcement, classical conditioning, loss-aversion, over-confidence, self-serving biases, cognitive dissonance, altruism, subjective well-being, and hedonic adaptation. Economic concepts such as equilibrium, rational choice, utility maximization, Bayesian beliefs, game theory, and behavior under uncertainty are discussed in light of these phenomena.

This course will look at the various mechanisms of evolution, how these mechanisms work, and how change is measured. The course will begin by reviewing the evolutionary concepts of selection and speciation. The student will then learn to measure evolutionary change and look at the history of life according to the fossil record and a discussion of the broad range of life forms as they are currently classified. Upon completion of this course, students will be able to: define evolution and describe different types of selection; provide examples of microevolutionary forces and describe how they impact the genetics of populations; describe the Hardy-Weinberg principle and solve problems related to Hardy-Weinberg equilibrium; provide examples of games used in evolutionary game theory; connect biological phenomena to game theory; develop simple phylogenies from molecular or morphological data; identify important evolutionary events that have occurred throughout geologic time; characterize and provide examples of major plant and animal phyla. (Biology 312)

In this exercise students investigate the possibility of cooperative behavior to arise among unrelated individuals even in the presence of selfish individuals or individuals that do not care for the well- being of other organisms with which they interact. Is it possible for individuals to obtain the benefits of mutual cooperation but at the same time protect themselves from cheaters? Students play a game among themselves where they use a number of different strategies that are either cooperative or selfish. They will learn basic concepts of game theory and use these to examine the evolution of cooperative behavior. A computer simulation is available where students can expand the range of possibilities that are offered to them during the laboratory exercise.

This course is an introduction to game theory and strategic thinking. Ideas such as dominance, backward induction, Nash equilibrium, evolutionary stability, commitment, credibility, asymmetric information, adverse selection, and signaling are discussed and applied to games played in class and to examples drawn from economics, politics, the movies, and elsewhere.

How should economic agents act when their optimal decisions depend on what they expect other agents to do? We study various models of equilibrium, which correspond to different ways that the agents might make their decisions, and various kinds of gamesstatic games, dynamic games, and games of incomplete information.

This is a standard course in "game theory," designed with the School of Information MSI students as the primary audience. This course is the pre-requisite for several ICD courses. To be well-prepared for management, policy and analysis in the information professions you need to first have a solid grounding in game theory and its applications to problem solving. Thus, the primary objective is to teach you a set of useful theories and how to apply them to solve problems. The emphasis is on method and application.

Increasingly, political scientists are using game theory to analyze strategic interactions across many different settings. Each of the sub-fields, to differing degrees, has seen game theoretic concepts enter its vocabulary, and students entering the profession will need to understand the potential and limits of game theory. This course aims to give students an entry-level understanding of the basic concepts of game theory, and how these concepts have been applied to the study of political phenomena. Because an important component of game theory in political science and political economy is the analysis of substantive political phenomena, we will cover illustrative examples each week in combination with methodological developments. The political and economic phenomena that we will examine include legislative rules, nuclear deterrence, electoral competition, and imperfect markets.

This half-term course examines the choices that we make which affect others and the choices others make that affect us. Such situations are known as "games" and game-playing, while sounding whimsical, is serious business. Managers frequently play games both within the firm and outside it - with competitors, customers, regulators, and even capital markets! The goal of this course is to enhance your ability to think strategically in complex, interactive environments. Knowledge of game theory will give you an advantage in such strategic settings. The course is structured around three "themes for acquiring advantage in games": commitment / strategic moves, exploiting hidden information, and limited rationality.

This course is an introduction to the fundamentals of game theory and mechanism design. Motivations are drawn from engineered/networked systems (including distributed control of wireline and wireless communication networks, incentive-compatible/dynamic resource allocation, multi-agent systems, pricing and investment decisions in the Internet), and social models (including social and economic networks). The course emphasizes theoretical foundations, mathematical tools, modeling, and equilibrium notions in different environments.

This course surveys major topics and theories in the field of Industrial Organization. As part of the applied microeconomics structure, Industrial Organization uses the basic tools of microeconomic theory and game theory to study the structure and behavior of firms and their strategic interactions with one another in the marketplace. Industrial Organization also studies the impact that those interactions have on market structure and welfare. This course will emphasize market structure analysis and the strategic behaviors of competing firms, including (but not limited to) product differentiation, collusion, price discrimination, pricing strategy, non-price discrimination (i.e. advertising), horizontal mergers, vertical integration, and vertical restraints. Upon successful completion of this course, students will be able to: Identify different theories of the firm; Describe the different market structures under which firms operate, with particular emphasis on concentration and monopoly power as well as oligopoly; Analyze how market structures impact the behavior of firms; Identify and compare the anti-competitive pricing strategies that firms adopt under various market structures; Use the theoretical insights presented in this course to explain observed features of particular markets and industries; Apply a deepened knowledge of game theory to understand the strategic behavior of firms in the market; Determine the factors that influence the firm's decision-making over time; Critically analyze the role of the government in regulating industries and the subsequent implications of public regulation. (Economics 306)

This is a course in industrial organization, the study of firms in markets. Industrial organization focuses on firm behavior in imperfectly competitive markets, which appear to be far more common than the perfectly competitive markets that were the focus of your basic microeconomics course. This field analyzes the acquisition and use of market power firms, strategic interactions among firms, and the role of government competition policy. We will approach this subject from both theoretical and applied perspectives.

Archive of 21 lectures in introductory game theory, from a course I delivered in semester 1 at the University of Canterbury NZ Feb to June 2007

We will explore the mathematical strategies behind popular games, toys, and puzzles. Topics covered will combine basic fundamentals of game theory, probability, group theory, and elementary programming concepts. Each week will consist of a lecture and discussion followed by game play to implement the concepts learned in class.

This course offers an introduction to noncooperative game theory. The course is intended both for graduate students who wish to develop a solid background in game theory in order to pursue research in the applied fields of economics and related disciplines, and for students wishing to specialize is economic theory. While the course is designed for graduate students in economics, it is open to all students who have taken and passed 14.121. The recommended primary text for the course is Drew Fudenberg and Jean Tirole's text, Game Theory. The text covers all the material in the course and much more, but has less in the way of intuition and examples than some students would like. For this reason, students might alternately wish to use Robert Gibbons' Game Theory for Applied Economists as their primary reference. Gibbons' book contains more readable discussions of the material and a lot of nice examples, but omits a few of the topics we'll cover. The course will be graded on the basis of five problem sets and a three hour final exam. In order to learn the material it is absolutely essential to do the problem sets. The problem sets will count for approximately one-fourth of the course grade.