Catálogo de publicaciones - libros

In this article we present an for task scheduling in a grid-like computer system. The scheduler allows to one such as CPU time, communication bandwidth, volatile and non-volatile memory by employing a combinatorial resource allocation mechanism. The allocation is performed by an in which try to acquire their desired resource allocation profiles with respect to limited monetary budget endowments. To achieve an efficient allocation process, the auctioneer provides to the bidders. We use a pricing mechanism based on shadow prices in a system in which the agents use monetary units awarded for the resources they provide to the system for the acquisition of complementary capacity. Our objective is to identify optimal bidding strategies in the multi-agent setting with respect to varying preferences in terms of resource quantity and waiting time for the resources. Based on a utility function we characterize two types of agents: a with a low preference for fast bid acceptance and an with a high valuation of fast access to the resources. By evaluating different strategies with varying initial bid pricing and price increments, it turns out that for quantity maximizing agents patience and low initial bids pay off, whereas impatient agents should avoid high initial bid prices.

Sequential and simultaneous auctions are two important mechanisms for buying/selling multiple objects. These two mechanisms yield different outcomes (i.e., different revenues and also different profits to the winning bidders). Hence, both the auctioneer and the bidding agents want to know which mechanism is better for them. Given this, we compare the outcomes for these mechanisms for the following scenario. There are multiple similar objects for sale, each object is sold in a separate auction, and each bidder needs only one object. We use English auction rules and first determine equilibrium bidding strategies for each individual auction for the simultaneous and sequential cases. We do this for both common and private value objects by treating a bidder’s information about these values as . We then consider the case where the private and common values have a uniform distribution and compare the two mechanisms in terms of three key properties: a bidder’s ex-ante expected profit, the auctioneer’s expected cumulative revenue, and the total expected surplus. For both common and private value objects, our study shows the following result. The expected cumulative revenue and the expected total surplus is higher for the sequential mechanism. However, a bidder’s exante expected profit depends on the number of objects being auctioned and the number of participating bidders, and it is sometimes higher for the sequential mechanism and sometimes for the simultaneous one.

We propose a novel method to characterize the performance of autonomous agents in the Trading Agent Competition for Supply Chain Management (TAC-SCM). We create a suite of testing tools that reduce the variability of TAC-SCM games, make them replayable, and generate specific market conditions under which autonomous trading agents can be tested. Using these tools, we show how developers can inspect their agents to reveal and correct undesirable behaviors that might otherwise have gone undiscovered. We also discuss how these tools can be used to improve overall trading agent performance in future competitions.

In this paper, we consider competition between sellers offering similar items in concurrent online auctions, where each seller must set its individual auction parameters (such as the reserve price) in such a way as to attract buyers. We show that in the case of two sellers with asymmetric production costs, there exists a pure Nash equilibrium in which both sellers set reserve prices above their production costs. In addition, we show that, rather than setting a reserve price, a seller can further improve its utility by shill bidding (i.e., pretending to be a buyer in order to bid in its own auction). But, through the use of an evolutionary simulation, we show that this shill bidding introduces inefficiences within the market. However, we then go on to show that these inefficiences can be reduced when the mediating auction institution uses appropriate auction fees that deter sellers from submitting shill bids. Specifically, we compare two types of auction fees and show that, in this respect, those based on the difference between the closing price and the reserve price are more effective than the commonly used fees that are based on closing price alone.

Online reputation mechanisms need honest feedback to function effectively. Self interested agents report the truth only when explicit rewards offset the cost of reporting and the potential gains that can be obtained from lying. Payment schemes (monetary rewards for submitted feedback) can make truth-telling rational based on the correlation between the reports of different clients.

In this paper we use the idea of automated mechanism design to construct the best (i.e., budget minimizing) incentive-compatible payments that are also robust to some degree of private information.

The Trading Agent Competition (TAC) is an international forum which promotes high quality research regarding the trading agent problem. One of the TAC competitive scenarios is Supply Chain Management (SCM) where six agents compete by buying components, assembling PCs from these components and selling the assembled PCs to customers. In this paper, we describe the strategies implemented in the CrocodileAgent, our entry in 2005 TAC SCM. We describe the structure and functionalities of the CrocodileAgent, the implementation of the basic agent tasks, and algorithms for ordering components and determining the profit margin. The agent’s performances in the 2005 TAC SCM competition, as well as in a series of controlled experiments, are discussed.

This paper presents a fuzzy constraint based model for bilateral multi-attribute agent purchase negotiations in competitive trading environments. Fuzzy constraints are used to capture requirements and to express proposals. The proposed interaction protocol is a dialogue game protocol where argumentation is used as a key mechanism to improve agreements in contrast to other fuzzy constraint based models which are limited to quantitative offers and counter-offers. A set of locutions and decision mechanisms which fire them are fully specified, so that each agent may decide its degree of cooperation and its degree of expressiveness, which in turn may have effects on the quality of the agreement. The notions of similarity and expected valuations of products are used in order to design efficient decision mechanisms. An example of a purchase scenario and a summary of statistical tests are presented to demonstrate the proposed model.