This textbook for advanced undergraduate and postgraduate students of Evolutionary Game Theory covers recent developments in the field, with an emphasis on economic contexts and applications. It begins with the basic ideas as they originated within the field of theoretical biology and then proceeds to the formulation of a theoretical framework that is suitable for the study of social and economic phenomena from an evolutionary perspective. Core topics include the Evolutionary Stable Strategy (EES) and Replicator Dynamics (RD), deterministic dynamic models, and stochastic perturbations. A set of short appendices presents some of the technical material referred to in the main text. Evolutionary theory is widely viewed as one of the most promising appraoches to understanding bounded rationality, learning, and change in complex social environments. New avenues of research are suggested by Vega-Redondo, and plentiful exmples illustrate the theory's potential applications. The recent boom experienced by this dscipline makes the book's systematic presentation of its essential contributions vital reading for newcomer to the field.

This 2007 book provides a systematic and self-contained account of the fast-developing theory of complex social networks. Social networks are central to the understanding of most socio-economic phenomena in the modern world. The classical approach to studying them relies on a methodology that abstracts from their size and complexity. In contrast, the approach taken in this book keeps complexity at the core, whilst integrating it with the incentive considerations that are preeminent in traditional economic analysis. The treatment starts with a detailed discussion of the basic models that act as 'benchmarks' for the complex-network literature: random networks, small worlds, and scale-free networks, before studying three different forces that underlie almost all network phenomena in social contexts: diffusion, search, and play. Finally, these forces are combined into a unified framework that is brought to bear on the issue of network formation and the coevolution of agents' behaviour and their pattern of interaction.

This 2007 book provides a systematic and self-contained account of the fast-developing theory of complex social networks. Social networks are central to the understanding of most socio-economic phenomena in the modern world. The classical approach to studying them relies on a methodology that abstracts from their size and complexity. In contrast, the approach taken in this book keeps complexity at the core, whilst integrating it with the incentive considerations that are preeminent in traditional economic analysis. The treatment starts with a detailed discussion of the basic models that act as 'benchmarks' for the complex-network literature: random networks, small worlds, and scale-free networks, before studying three different forces that underlie almost all network phenomena in social contexts: diffusion, search, and play. Finally, these forces are combined into a unified framework that is brought to bear on the issue of network formation and the coevolution of agents' behaviour and their pattern of interaction.

Fernando Vega-Redondo's self-contained account of the main contributions of modern game theory and its applications to economics starts with a detailed description of how to model strategic situations. The discussion proceeds by studying basic solution concepts and their main refinements; games played under incomplete information; and repeated games. For each of these theoretical developments, the text includes a companion set of applications that cover the most representative instances of game-theoretic analysis in economics (e.g., oligopolistic competition, public goods, coordination failures, bargaining, insurance markets, implementation theory, signaling and auctions).

Fernando Vega-Redondo's self-contained account of the main contributions of modern game theory and its applications to economics starts with a detailed description of how to model strategic situations. The discussion proceeds by studying basic solution concepts and their main refinements; games played under incomplete information; and repeated games. For each of these theoretical developments, the text includes a companion set of applications that cover the most representative instances of game-theoretic analysis in economics (e.g., oligopolistic competition, public goods, coordination failures, bargaining, insurance markets, implementation theory, signaling and auctions).

Evolution and learning in games is a topic of current intense interest. Evolution theory is widely viewed as one of the most promising approaches to understanding learning, bounded rationality, and change in complex social environments. This graduate textbook covers the recent developments with an emphasis on economic contexts and applications. Covering both deterministic and stochastic evolutionary dynamics which play an important role in evolutionary processes, it also includes the recent stochastic evolutionary framework that has been developed (and applied widely) in the last few years. The recent boom experienced by this discipline makes this book's systematic presentation of its essential contributions, using mathematical knowledge only when required, especially useful for any newcomer to the field. Packed with numerous economic applications of the theory, with suggestions for new avenues of research, it will prove invaluable to postgraduate economists.