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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

While English auctions are the most common in practice, their rules typically lack sufficient structure to yield a tractable theoretical model without significant abstractions. Rather than relying on one stylized model to provide an exact interpretation of the data, we explore an incomplete model based on two simple assumptions: bidders neither bid more than their valuations nor let an opponent win at a price they would be willing to beat. Focusing on the symmetric independent private values paradigm, we show that this limited structure enables construction of informative bounds on the distribution function char-acterizing bidder demand, on the optimal reserve price, and on the effects of observable covariates on bidder valuations. If the standard theoretical model happens to be the true model, our bounds collapse to the true features of interest. In contrast, when the true data-gen-erating process deviates in seemingly small ways from that implied by equilibrium in the standard theoretical model, existing methods can yield misleading results that need not even lie within our bounds. We report results from Monte Carlo experiments illustrating the perform-ance of our approach and comparing it to others. We apply our ap-

In the field of economics, perhaps the most important break with the past—one that leaves open huge areas for future work—lies in the economics of information. It is now recognized that information is imperfect, obtaining informa-tion can be costly, there are important asymmetries of information, and the extent of information asymmetries is affected by actions of firms and individuals. This recognition deeply affects the understanding of wisdom inherited from the past, such as the fundamental welfare theorem and some of the basic characterization of a market economy, and provides explanations of economic and social phenomena that otherwise would be hard to understand. I.

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We develop tests for common values at first-price sealed-bid auctions. Our tests are nonparametric, require observation only of the bids submitted at each auction, and are based on the fact that the “winner’s curse” arises only in common values auctions. The tests build on recently developed methods for using observed bids to estimate each bidder’s conditional expectation of the value of winning the auction. Equilibrium behavior implies that in a private values auction these expectations are invariant to the number of opponents each bidder faces, while with common values they are decreasing in the number of opponents. This distinction forms the basis of our tests. We consider both exogenous and endogenous variation in the number of bidders. Monte Carlo experiments show that our tests can perform well in samples of moderate sizes. We apply our tests to two different types of U.S. Forest Service timber auctions. For unit-price (“scaled”) sales often argued to fit a private values model, our tests consistently fail to find evidence of common values. For “lumpsum” sales, where aprioriarguments for common values appear stronger, our tests yield mixed evidence against the private values hypothesis.

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We describe mechanisms for auctions that are simultaneously truthful (alternately known as strategy-proof or incentive-compatible) and guarantee high "net" profit. We make use of appropriate variants of competitive analysis of algorithms in designing and analyzing our mechanisms. Thus, we do not require any probabilistic assumptions on bids. We present

... widespread, standardisation of ontologies, message content and message protocols will be necessary. In this paper, we present a lifecycle of a business-to-business e-commerce interaction, and show how the Semantic Web can support a service description language that can be used throughout this lifecycle. By using DAML+OIL, we develop a service description language sufficiently expressive and flexible to be used not only in advertisements, but also in matchmaking queries, negotiation proposals and agreements. We also identify which operations must be carried out on this description language if the B2B lifecycle is to be fully supported. We do not propose specific standard protocols, but instead argue that our operators are able to support a wide variety of interaction protocols, and so will be fundamental irrespective of which protocols are finally adopted.

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