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Leigh Tesfatsion - One of the best experts on this subject based on the ideXlab platform.

  • Agent-Based Computational Economics: Modeling Economies As Complex Adaptive Systems
    2008
    Co-Authors: Leigh Tesfatsion
    Abstract:

    Agent-based Computational Economics (ACE) is the Computational study of economies modeled as dynamic systems of 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 disusses several active application areas. Annotated pointers to related work can be accessed here: http://www2.econ.iastate.edu/tesfatsi/ace.htm

  • Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics
    2006
    Co-Authors: Leigh Tesfatsion, Kenneth L. Judd
    Abstract:

    This handbook comprises 16 chapters surveying agent-based Computational Economics research, 6 shorter essays providing personal perspectives, and a "getting started" guide for newcomers to agent-based modeling in the social sciences. Research topics covered include: learning representations for Computational agents; agent-based models and human-subject experiments; economic activity on fixed networks; endogenous formation of economic networks; social dynamics and the evolution of norms; heterogenous agent modeling in Economics and finance; agent-based Computational finance; agent-based models of innovation and technological change; agent-based models of organizations; market design using agent-based models; automated markets and trading agents; agent-based Computational methods and models of politics; agent-based tools for exploring the governance of social-ecological systems; and Computational laboratories for spatial agent-based modeling. Related work can be accessed at http://www2.econ.iastate.edu/tesfatsi/ace.htm

  • Agent-Based Computational Economics: A Constructive Approach to Economic Theory
    Handbook of Computational Economics, 2006
    Co-Authors: Leigh Tesfatsion
    Abstract:

    Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and Computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE), the Computational study of economic processes modeled as dynamic systems of interacting agents. This chapter explores the potential advantages and disadvantages of ACE for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, institutional arrangements, and behavioral dispositions.

  • Agent-based Computational Economics: modeling economies as complex adaptive systems
    Information Sciences, 2003
    Co-Authors: Leigh Tesfatsion
    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 paper outlines the main objectives and defining characteristics of the ACE methodology, and discusses several active research areas.

  • Agent-based Computational Economics
    Computational Economics, 2002
    Co-Authors: Leigh Tesfatsion
    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 study 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.

Shu-heng Chen - One of the best experts on this subject based on the ideXlab platform.

  • Oxford Handbooks Online - Computational Economics in the Era of Natural Computationalism
    Oxford Handbooks Online, 2018
    Co-Authors: Shu-heng Chen, M. A. Kaboudan
    Abstract:

    After a brief review of natural Computationalism, this introductory chapter presents a new skeleton of Computational Economics and finance (CEF) along with an overview of the handbook. It begins with a conventional pursuit focusing on the algorithmic or numerical aspect of CEF such as Computational efforts devoted to rational expectations, (dynamic) general equilibrium, and volatility. It then moves toward an automata- or organism-based perspective of CEF, involving nature-inspired intelligence, algorithmic trading, automated markets, network- and agent-based computing, and neural computing. As an alternative way to introduce this novel skeleton, the chapter starts with a view of computation or computing, addressing what Computational Economics intends to compute and what kinds of Economics make computation so hard, and then it turns to a view of computing systems in which the Walrasian kind of Computational Economics is replaced by the Wolframian kind due to Computational irreducibility.

  • Decision Economics@DCAI - The Missing Legacy of Herbert Simon in Agent-Based Computational Economics
    Advances in Intelligent Systems and Computing, 2016
    Co-Authors: Shu-heng Chen
    Abstract:

    In this article, we examine the legacy of Simon in Agent-Based Computational Economics (ACE). We show that both near decomposability and modularity, the two essential ingredients of the Simonian Economics, have not been seriously pursued by the ACE community. First, most ACE models are not endogenously multi-level, which makes near decomposability be not much relevant to ACE. Second, while the modularity approach has already been employed by Simon in his artificial intelligence research and can help shape a notion of autonomous agents, this approach is also not well followed by the ACE community. Instead, most artificial agents used in ACE have been put in rather identically repeated environment not much different what the movie “Groundhog Day” depicts [23]. Hence, they are not able to do serious novelty or chance discovery, and the creativity of artificial agents have not been taken seriously by most ACEers.

  • Herbert Simon and Agent-Based Computational Economics
    Minds Models and Milieux, 2016
    Co-Authors: Shu-heng Chen, Ying-fang Kao
    Abstract:

    Herbert Simon was a quintessential interdisciplinary scholar who made pioneering contributions concerning the notion of bounded rationality, built models based on it, and made important advances in understanding complex systems. His importance in the field of artificial intelligence, which was in turn the inspiration of agent-based Computational Economics (ACE), is discussed in detail in Chen (2005). Among all the Nobel Laureates in Economics, there are at least three whose work has been acknowledged by the ACE community. They are Friedrich Hayek (1899–1992), Thomas Schelling (1921-), and Elinor Ostrom (1933–2012). The last two worked directly on ACE. Schelling’s celebrated work on the segregation model is considered one of earliest publications on ACE (Schelling, 1971). Ostrom contributed to the development of empirical agent-based models (Janssen and Ostrom, 2006). Hayek did not work on ACE, but the connection of his work to ACE has been pointed out by Vriend (2002).

  • the missing legacy of herbert simon in agent based Computational Economics
    Decision Economics@DCAI, 2016
    Co-Authors: Shu-heng Chen
    Abstract:

    In this article, we examine the legacy of Simon in Agent-Based Computational Economics (ACE). We show that both near decomposability and modularity, the two essential ingredients of the Simonian Economics, have not been seriously pursued by the ACE community. First, most ACE models are not endogenously multi-level, which makes near decomposability be not much relevant to ACE. Second, while the modularity approach has already been employed by Simon in his artificial intelligence research and can help shape a notion of autonomous agents, this approach is also not well followed by the ACE community. Instead, most artificial agents used in ACE have been put in rather identically repeated environment not much different what the movie “Groundhog Day” depicts [23]. Hence, they are not able to do serious novelty or chance discovery, and the creativity of artificial agents have not been taken seriously by most ACEers.

  • NeuroEconomics and Agent-Based Computational Economics
    International Journal of Applied Behavioral Economics, 2014
    Co-Authors: Shu-heng Chen
    Abstract:

    Recently, the relation between neuroEconomics and agent-based Computational Economics (ACE) has become an issue concerning the agent-based Economics community. NeuroEconomics can interest agent-based economists when they are inquiring for the foundation or the principle of the software-agent design. It has been shown in many studies that the design of software agents is non-trivial and can determine what will emerge from the bottom. Therefore, it has been quested for rather a period regarding whether anyone can sensibly design these software agents, including both the choice of software agent models, such as reinforcement learning, and the parameter setting associated with the chosen model, such as risk attitude. In this paper, the author will start a formal inquiry by focusing on examining the models and parameters used to build software agents.

Kexin Zhao - One of the best experts on this subject based on the ideXlab platform.

  • diffusion dynamics of open source software an agent based Computational Economics ace approach
    Decision Support Systems, 2011
    Co-Authors: Muhammad Adeel Zaffar, Ram L Kumar, Kexin Zhao
    Abstract:

    The rising popularity of open source software (OSS) calls for a better understanding of the drivers of its adoption and diffusion. In this research, we propose an integrated framework that simultaneously investigates a broad range of social and economic factors on the diffusion dynamics of OSS using an Agent Based Computational Economics (ACE) approach. We find that interoperability costs, variability of OSS support costs, and duration of PS upgrade cycle are major determinants of OSS diffusion. Furthermore, there are interaction effects between network topology, network density and interoperability costs, which strongly influence the diffusion dynamics of OSS. The proposed model can be used as a building block to further investigate complex competitive dynamics in software markets.

Hans M. Amman - One of the best experts on this subject based on the ideXlab platform.

  • Computational Economics: Help for the Underestimated Undergraduate
    Computational Economics, 2006
    Co-Authors: David A. Kendrick, P. Ruben Mercado, Hans M. Amman
    Abstract:

    Computational Economics, undergraduate Economics, teaching Economics,

  • Computational Economics: Help for the Underestimated Undergraduate
    Computing in Economics and Finance, 2006
    Co-Authors: David A. Kendrick, P. Ruben Mercado, Hans M. Amman
    Abstract:

    Our concern in this paper is that the capability of Economics undergraduates is substantially underestimated in the design of the present college curriculum and that our students are insufficiently challenged and motivated. Students enter our classrooms with substantial previous knowledge about computers and computation and we are not taking full advantage of this opportunity. We suggest a set of examples from Computational Economics which are challenging enough to motivate students and simple enough that they can master them within a few hours. By encouraging the students to modify the models in directions of their own interest, avenues for creative endeavor are opened which deeply involve the students in their own education.

  • What is Computational Economics
    Computing in Economics and Finance, 1997
    Co-Authors: Hans M. Amman
    Abstract:

    Computational Economics is rapidly evolving into an independent branche in Economics. This paper describes the current and future developments within the field of Computational Economics.

  • Handbook of Computational Economics
    1996
    Co-Authors: Hans M. Amman, John Rust, David A. Kendrick
    Abstract:

    Preface. Economic Topics. Computable general equilibrium modelling for policy analysis and forecasting (P.B. Dixon, B.R. Parmenter). Computation of equilibria in finite games (R.D. McKelvey, A. McLennan). Computational methods for macroeconomic models (R.C. Fair). Mechanics of forming and estimating dynamic linear economies (E.W. Andersen et al.). Nonlinear pricing and mechanism design (R. Wilson). Sectoral Economics (D.A. Kendrick). Computer Science Parallel computation (A. Nagurney). Artificial intelligence in Economics and finance: A state of the art - 1994 (L.F. Pau, P.-Y. Tan). Neural networks for encoding and adapting in dynamic economies (I.-K. Cho, T.J. Sargent). Modelling languages in Computational Economics: GAMS (S.A. Zenios). Numerical Methods. Mathematica for economists (H. Varian). Approximation, perturbation, and projection methods in economic analysis (K.L. Judd). Numerical methods for linear-quadratic models (H.M. Amman). Numerical dynamic programming in Economics (J. Rust). Monte Carlo simulation and numerical integration (J. Geweke).

  • Computational Economics and econometrics
    1992
    Co-Authors: Hans M. Amman, David A Belsley, Louisfrancois Pau
    Abstract:

    One: Econometrics.- Likelihood evaluation for dynamic latent variables models.- Global optimization of statistical functions: Preliminary results.- On efficient exact maximum likelihood estimation of high-order multivariate ARMA models.- Efficient computation of stochastic coefficients models.- The degree of effective identification and a diagnostic measure for assessing it.- Two: Model stimulation and Optimization.- A splitting equilibration algorithm for the computation of large-scale constrained matrix problems: Theoretical analysis and applications.- Nonstationary model solution techniques and the USA algorithm.- Implementing no-derivative optimizing procedures for optimization of econometric models.- Information in a Stackelberg game between two players holding different theoretical views: Solution concepts and an illustration.- Exchange rate uncertainty in imperfect markets: A simulation approach.- Authors' index.

Muhammad Adeel Zaffar - One of the best experts on this subject based on the ideXlab platform.

  • diffusion dynamics of open source software an agent based Computational Economics ace approach
    Decision Support Systems, 2011
    Co-Authors: Muhammad Adeel Zaffar, Ram L Kumar, Kexin Zhao
    Abstract:

    The rising popularity of open source software (OSS) calls for a better understanding of the drivers of its adoption and diffusion. In this research, we propose an integrated framework that simultaneously investigates a broad range of social and economic factors on the diffusion dynamics of OSS using an Agent Based Computational Economics (ACE) approach. We find that interoperability costs, variability of OSS support costs, and duration of PS upgrade cycle are major determinants of OSS diffusion. Furthermore, there are interaction effects between network topology, network density and interoperability costs, which strongly influence the diffusion dynamics of OSS. The proposed model can be used as a building block to further investigate complex competitive dynamics in software markets.

  • An exploration of the diffusion dynamics of open source software (oss): an agent-based Computational Economics (ace) approach
    2010
    Co-Authors: Ram L Kumar, Muhammad Adeel Zaffar
    Abstract:

    Despite the rising popularity of Open Source Software (OSS), there is limited understanding of the factors that affect the diffusion of OSS at the organizational level. Review of the literature suggests that previous empirical and analytical studies on this subject matter though valuable in their own respect, either did not address the full spectrum of critical factors in one model or did not investigate the impact of critical factors in enough detail leaving some gaps in the literature. In an effort to bridge these gaps, this dissertation develops a model to (a) jointly investigate the effect of critical variables other than price on the diffusion dynamics of OSS, (b) investigate the effects of social networks or inter-organizational relationships on the diffusion dynamics of OSS, (c) propose a new software price discounting scheme and compare its effectiveness against traditional software price discounting schemes on the diffusion dynamics of OSS. An Agent-Based Computational Economics (ACE) approach is adopted to develop a comprehensive simulation model to investigate the aforementioned research problems. Although, desktop operating system software is used as an exemplar to investigate the diffusion of its open source and proprietary alternatives, the framework proposed in the dissertation is general enough to be applied in the investigation of diffusion of other kinds of software as well.