Abstract: Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Thus, ACE is a specialization to economics of the basic complex adaptive systems paradigm. This study outlines the main objectives and defining characteristics of the ACE methodology, and discusses similarities and distinctions between ACE and artificial life research. Eight ACE research areas are identified, and a number of publications in each area are highlighted for concrete illustration. Open questions and directions for future ACE research are also considered. The study concludes with a discussion of the potential benefits associated with ACE modeling, as well some potential difficulties. Keywords: Agent-based computational economics; artificial life; learning; evolution of norms; markets; networks; parallel experiments with humans and computational agents; computational laboratories. 1

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This article develops a model of organizational knowledge acquisition in terms of modern psychological, sociological, economic and management theories by deconstructing the terms involved: an organization as a collective agent having goals and capabilities to achieve them; knowledge as the hidden state variables imputed to an agent as the basis of its capabilities; and acquisition as the reproduction of dispositions. This form of model enables one to relate the knowledge processes involved to existing models of organizational processes, and to understand such phenomena as knowledge economics and knowledge management. The breadth of the notion of organization encompasses markets, firms and societies; the operational definition of knowledge clarifies its role and the utility of the notion; and the focus on reproduction of dispositions in knowledge acquisition enables the management of knowledge acquisition to be analyzed. ______________________________________________________________________________________ 1.

This article outlines the motivation for a spatial approach as a novel focus for cross-disciplinary interaction and research in the social and behavioral sciences. The authors review the emerging interest in space and place in the recent social science literature and develop a vision for a spatially integrated social science. This vision provides the conceptual basis for a program of six activities designed to promote a spatial perspective: learning resources, workshops, bestpractice examples, place-based search, software tools, and a virtual community. The six programs will be informed by advances in the methods, technologies, and principles underlying spatial information science. The analysis of space and place has become an increasingly pivotal component of social science research in the past two decades. In part, this can be attributed to the transformation of social space around the globe, accompanied by shifts of varying degrees of magnitude in social science conceptualizing and theorizing. One aspect of these changes is subsumed under the general notion of “space-time compres-This article is a revised and shortened version of a proposal to the U.S. National Science Foundation (NSF) titled “SPESS: A Center for Spatially Enabled Social Science, ” which resulted in a five-year

Abstract: Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Starting from initial conditions, specified by the modeler, the computational economy evolves over time as its constituent agents repeatedly interact with each other and learn from these interactions. ACE is therefore a bottom-up culture-dish approach to the study of economic systems. This chapter discusses the key characteristics and goals of the ACE methodology. Eight currently active research areas are highlighted for concrete illustration. Potential advantages and disadvantages of the ACE methodology are considered, along with open questions and possible directions for future research. Keywords: Agent-based computational economics; autonomous agents; interaction networks; learning; evolution; mechanism design; computational experiments; object-oriented programming. 1

This study investigates the performance of Gale-Shapley matching in an evolutionary market context. Computational experimental findings are reported for an evolutionary match-and-play trade network game in which resource-constrained traders repeatedly choose and refuse trade partners in accordance with Gale-Shapley matching, participate in risky trades modelled as two-person prisoner’s dilemma games, and evolve their trade behavior over time. Particular attention is focused on correlations between ex ante market structure and the formation of trade networks, and between trade network formation and the types of trade behavior and social welfare outcomes that these trade networks support.

this paper because we assume throughout that the total initial wealth of all systems of agents is $1

Agent-based computational economics (ACE) is the computational study of economies modelled as evolving systems of autonomous interacting agents. Thus, ACE is a specialization to economics of the basic complex adaptive systems paradigm. This paper outlines the main objectives and defining characteristics of the ACE methodology, and discusses several active research areas. Key words: Agent-based computational economics, complex adaptive systems 1

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