Modeling economic systems as locally-constructive sequential games

Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a modeling approach, Agent-based Computational Economics, that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented and explained. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing

How Economists Can Get Alife

What, is artificial life, or alife for short? And why should economists cafe? • -As-detailed in the entertaining, monographs by Levy (1992) and =Sigmund (1993), the roots of-alife go at least as far back as the work-of.John von-Neumann, in.the nineteen forties on self-replicating automata.. The establishment of.alife as a distinct field of inquiry, however, must be traced to the first alife conference,lOrganized in 1987iby\u27Chris Langton at the Los Alamos NationalrLaboratory; see Langton (1989).

Agent-Based Computational Modeling And Macroeconomics

Agent-based Computational Economics (ACE) is the computational study of economic processes modeled as dynamic systems of interacting agents. This essay discusses the potential use of ACE modeling tools for the study of macroeconomic systems. Points are illustrated using an ACE model of a two-sector decentralized market economy. Related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/amulmark.htmagent-based computational economics

Agent-based Modeling and Institutional Design

The recent economic crisis has led to calls for a comprehensive restructuring of energy, financial, health care, and educational systems. Critics worry that the restructuring of these complex institutional arrangements could produce adverse unintended consequences. Given these concerns, pre-testing of proposed changes is eminently desirable but also exceedingly difficult. This essay focuses on the potential use of agent-based modeling for studying proposed changes in institutional arrangements in advance of actual implementation. Ongoing agent-based research on the restructuring of electric power markets is used for concrete illustration

Hysteresis in an Evolutionary Labor Market with Adaptive Search

This study undertakes a systematic experimental investigation of hysteresis (path dependency) in an agent-based computational labor market framework. It is shown that capacity asymmetries between work suppliers and employers can result in two distinct hysteresis effects, network and behavioral, when work suppliers and employers interact strategically and evolve their worksite behaviors over time. These hysteresis effects result in persistent heterogeneity in earnings and employment histories across agents who have no observable structural differences. At a more global level, these hysteresis effects are shown to result in a one-to-many mapping between treatment factors and experimental outcomes. These hysteresis effects may help to explain why excess earnings heterogeneity is commonly observed in real-world labor markets.Dynamic labor market, Hysteresis (path dependency), Networks, Endogenous Interactions, Agent-based computational economics, Evolutionary game.

Automatic Evaluation of Higher-Order Partial Derivatives for Nonlocal Sensitivity Analysis

This proceedings paper surveys work on the FEED (Fast Efficient Evaluation of Derivatives) algorithm originally developed by Kalaba, Tesfatsion, and Wang (1983), with particular reference to the use of FEED for the implementation of nonlocal automated sensitivity techniques; see the articles below. The relationship of FEED to the automatic differentiation algorithms developed by other SIAM Workshop participants is clarified. Related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/nasahome.htmAutomatic evaluation; higher-order partial derivatives; FEED; automated sensitivity analysis

Auction Basics for Wholesale Power Markets: Objectives and Pricing Rules

Power systems have distinctive features that greatly complicate the development of auction designs. This study reviews the theory and practice of auction design as it relates specifically to U.S. restructured wholesale power markets, i.e., centrally-administered wholesale power markets with congestion managed by locational marginal prices. Basic auction concepts such as reservation value, net seller surplus, net buyer surplus, competitive market clearing, market efficiency, market pricing rules, supply offers, demand bids, strategic capacity withholding, and market power are explained and illustrated. Complicating factors specific to wholesale power markets are clarified, and recent advances in computational tools designed to address these complications are briefly noted.market power; Auction markets; power systems; design; efficency; pricing rules; agent-based test beds

A Trade Network Game with Endogenous Partner Selection

This paper develops an evolutionary trade network game (TNG) that combines evolutionary game play with endogenous partner selection. Successive generations of resource-constrained buyers and sellers choose and refuse trade partners on the basis of continually updated expected payoffs. Trade partner selection takes place in accordance with a modified Gale-Shapley matching mechanism, and trades are implemented using trade strategies evolved via a standardly specified genetic algorithm. The trade partnerships resulting from the matching mechanism are shown to be core stable and Pareto optimal in each successive trade cycle. Nevertheless, computer experiments suggest that these static optimality properties may be inadequate measures of optimality from an evolutionary perspective. Related work can be accessed at: http://www.econ.iastate.edu/tesfatsi/tnghome.htmTrade network formation; evolutionary game; endogenous partner selection; iterated prisoner's dilemma; Gale-Shapley matching

An Evolutionary Trade Network Game With Preferential Partner Selection

An evolutionary trade network game (TNG) is proposed for studying the interplay between evolutionary game dynamics and preferential partner selection in various market contexts with distributed adaptive agents. The modular form of the TNG facilitates experimentation with alternative specifications for trade partner matching, trading, expectation updating, and trade strategy evolution. Experimental results obtained using a C-t-f implementation suggest that the conventional optimal properties used to evaluate agent matching mechanisms in static market contexts may be in an equate measures of optimal from an evolutionary perspective

Economic Systems as Constructively Rational Games: Oh, the Places We Could Go!

The first part of this presentation provides a brief but careful overview of agent-based computational economics (ACE), the computational modeling of economic processes (including whole economies) as open-ended dynamic systems of interacting agents. The potential applicability of ACE modeling for the study of economic systems is illustrated by means of an ACE macroeconomic study. Several key methodological issues are next highlighted: namely, empirical validation; standardized measures of model development; and standardized presentation protocols. The final part of the presentation considers how ACE modeling tools could be used to undertake edgier creative explorations of issues critical for the operation of real-world economic systems