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"This book provides an introduction to the role of diversity in complex adaptive systems. A complex system--such as an economy or a tropical ecosystem--consists of interacting adaptive entities that produce dynamic patterns and structures. Diversity plays a different role in a complex system than it does in an equilibrium system, where it often merely produces variation around the mean for performance measures. In complex adaptive systems, diversity makes fundamental contributions to system performance. Scott Page gives a concise primer on how diversity happens, how it is maintained, and how it affects complex systems. He explains how diversity underpins system level robustness, allowing for multiple responses to external shocks and internal adaptations; how it provides the seeds for large events by creating outliers that fuel tipping points; and how it drives novelty and innovation. Page looks at the different kinds of diversity--variations within and across types, and distinct community compositions and interaction structures--and covers the evolution of diversity within complex systems and the factors that determine the amount of maintained diversity within a system. Provides a concise and accessible introduction Shows how diversity underpins robustness and fuels tipping points. Covers all types of diversity The essential primer on diversity in complex adaptive systems."--GoogleBooks

"This book provides an introduction to the role of diversity in complex adaptive systems. A complex system--such as an economy or a tropical ecosystem--consists of interacting adaptive entities that produce dynamic patterns and structures. Diversity plays a different role in a complex system than it does in an equilibrium system, where it often merely produces variation around the mean for performance measures. In complex adaptive systems, diversity makes fundamental contributions to system performance. Scott Page gives a concise primer on how diversity happens, how it is maintained, and how it affects complex systems. He explains how diversity underpins system level robustness, allowing for multiple responses to external shocks and internal adaptations; how it provides the seeds for large events by creating outliers that fuel tipping points; and how it drives novelty and innovation. Page looks at the different kinds of diversity--variations within and across types, and distinct community compositions and interaction structures--and covers the evolution of diversity within complex systems and the factors that determine the amount of maintained diversity within a system. Provides a concise and accessible introduction Shows how diversity underpins robustness and fuels tipping points. Covers all types of diversity The essential primer on diversity in complex adaptive systems."--GoogleBooks

This book provides an introduction to the role of diversity in complex adaptive systems. A complex system--such as an economy or a tropical ecosystem--consists of interacting adaptive entities that produce dynamic patterns and structures. Diversity plays a different role in a complex system than it does in an equilibrium system, where it often merely produces variation around the mean for performance measures. In complex adaptive systems, diversity makes fundamental contributions to system performance. Scott Page gives a concise primer on how diversity happens, how it is maintained, and how it affects complex systems. He explains how diversity underpins system level robustness, allowing for multiple responses to external shocks and internal adaptations; how it provides the seeds for large events by creating outliers that fuel tipping points; and how it drives novelty and innovation. Page looks at the different kinds of diversity--variations within and across types, and distinct community compositions and interaction structures--and covers the evolution of diversity within complex systems and the factors that determine the amount of maintained diversity within a system. Provides a concise and accessible introduction Shows how diversity underpins robustness and fuels tipping points Covers all types of diversity The essential primer on diversity in complex adaptive systems.

I discuss the concept of complexity and the burgeoning field of complex systems and their relevance to sociology. I begin by comparing and contrasting various definitions of complexity and then describe the attributes of systems capable of producing complexity: diversity, networked interactions, interdependent behavior, and adaptation. Next, I survey the contributions of complexity sciences with the most resonance with sociology. I organize those contributions into four categories: dynamics, aggregation, distributions, and functional properties of structure and diversity. On the basis of that survey, I conclude that incorporating complexity science into sociology requires the introduction of new models and methodologies as well as a more expansive approach to empirical research, and that the benefits of a deeper engagement with complexity will be substantial.

The task of designing effective economic and political institutions requires substantial foresight. The designer must anticipate not only the behavior of individual actors, but also how that behavior will aggregate. Rising complexity brought about by increases in speeds of adaptation, diversity, connectedness, and interdependence make institutional design all the more challenging. Given the focus on equilibria, the extant literature on mechanism design might appear incapable of coping with this complexity. Yet, I suggest that a deeper engagement with the origins of the mechanism-design framework reveals insights that may help us design robust, adaptive institutions that can harness complexity.

In this article I clarify the often muddled distinctions between uncertainty, difficulty, and complexity and show that all three can enhance our understanding of institutional performance and design. To cope with uncertainty, institutions align incentives for information revelation; to handle difficult problems, institutions create incentives for diverse problem-solving approaches; and to harness complexity, institutions adjust selection criteria, rates of variation, and the level of connectedness. The distinction between complex systems and equilibrium systems also necessitates a discussion of the differences between the existence, stability, and attainment of equilibria and why, despite often being neglected, the latter two concepts are important to our understanding of institutions.

In this article I clarify the often muddled distinctions between uncertainty, difficulty, and complexity and show that all three can enhance our understanding of institutional performance and design. To cope with uncertainty, institutions align incentives for information revelation; to handle difficult problems, institutions create incentives for diverse problem-solving approaches; and to harness complexity, institutions adjust selection criteria, rates of variation, and the level of connectedness. The distinction between complex systems and equilibrium systems also necessitates a discussion of the differences between the existence, stability, and attainment of equilibria and why, despite often being neglected, the latter two concepts are important to our understanding of institutions. [Reprinted by permission of Sage Publications Ltd., copyright 2008.]

THis paper studies the relationship between voters' preferences and teh composition of party platforms in teh two-party democractice elections with adaptive parties. In the model, preferences determine an electoral landscape on which parties locally adapt platforms. Varying the distribution of voter's preferences alters the landscape's ruggedness and may effect parties' responsiveness. We find that in atwo-party democratic elections, adaptive parties genearlly locate in regions of high social utiliyt but cannot always find winning platforms. We also show that parties' ability to locate winning plaforms as well as teh rate of convergence of party platforms depends upon the

This paper introduces specialized elections. A specialized election randomly assigns each voter to one election, freeing her of voting responsibilities in other elections. By reducing voters' responsibilities, specialized elections encourage more information acquisition. Specialized elections also make campaigning less costly. A shortcoming of specialized elections is the increase in outcome variance resulting from the sampling effect. Whether or not specialized elections improve democratic outcomes hinges upon the tradeoff between more informed voters and greater outcome variance. Sufficient conditions are derived for the increase in information to generate an outcome nearer to that which would be chosen by a fully informed electorate.

We develop a model of spatial elections that departs from the standard model in three important respects. Our parties' information of voters' preferences is limited to polls; our parties can be either office-seeking of ideological; and our parties are not perfect optimizers, i.e. they are modeled as boundedly rational actors. Since our imperfect parties do not necessarily find optimal positions, rather than concern ourselves with existence and location of equilibria, we trace the trajectory of winning party positions. The outcomes are subsequently evaluated with respect to a measure of social welfare, centrality. Our results suggest that in fair voting systems, two party elections lead to normatively appealing outcomes. We are seeking to introduce the role of computers genearlly and adaptive artificial agents (AAA) specifically, to the study of parties, voters, and elections in spatial models. We argue for using adaptive parties to add behavioral complexity to stand formal models of politics without sacrificing a logical foundation. Doing so may not only revise our judgments about the relevance of spatial voting models to real elections, but it may lead us to important insights about what occurs in those elections.