We analyze a repeated first-price auction in which the types of the players are determined before the first round. It is proved that if every player is using either a belief-based learning scheme with bounded recall or a generalized fictitious play learning scheme, then for sufficiently large...

In this paper we consider equilibrium behavior in a Dutch (descending price) auction where the bidders are uninformed of their valuations with probability 1-q and can acquire information about their valuation at a positive cost during the auction. We assume that the information acquisition...

The role of automated agents in the electronic marketplace has been growing steadily and has been attracting a lot of research from the artificial intelligence community as well as from economists. We consider the problem of homogeneous sellers of a single raw material or component vying for...

Agent-based simulations are performed to study adaptive learning in the context of asymmetric first-price auctions. Non-linearity of the Nash equilibrium strategies is used to investigate the effect of task complexity on adaptive learning by varying the degree of approximation the agents can...

The auctioning of frequency has to comply with a multitude of requirements in order to guarantee a transparent and efficient process. The German Federal Network Agency (Bundesnetzagentur) has opted for a design that provides participants with information on the highest bid after each round for...

In this study, we designed a delayed payment mechanism in laboratory second price auctions (SPAs) under which subjects received a cash endowment two weeks after the experiment day and had to use their own money to pay the experimental loss (if any) on the experiment day. We compared the effect...

This experiment examines forecasting behavior under varying information conditions to assess the extent to which traders in security markets incorporate information in trading activity to resolve fundamental uncertainty and to resolve higher-order uncertainty. Fundamental uncertainty refers to a...

This chapter explores the state of the emerging practice of designing markets by the use of agent-based modeling, with special reference to electricity markets and computerized (on-line) markets, perhaps including real-life electronic agents as well as human traders. The paper first reviews the...

We study the revenue-maximizing mechanism when a buyer’s value evolves endogenously because of learning-by-consuming. A seller sells one unit of a divisible good, while the buyer relies on his private, rough valuation to choose his first-stage consumption level. Consuming more leads to a more...