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Parsons S.,Brooklyn College | Rodriguez-Aguilar J.A.,Institute dInvestigacio en Intelligencia Artificial | Klein M.,Massachusetts Institute of Technology
ACM Computing Surveys | Year: 2011

There is a veritable menagerie of auctions-single-dimensional, multi-dimensional, single-sided, double-sided, first-price, second-price, English, Dutch, Japanese, sealed-bid-and these have been extensively discussed and analyzed in the economics literature. The main purpose of this article is to survey this literature from a computer science perspective, primarily from the viewpoint of computer scientists who are interested in learning about auction theory, and to provide pointers into the economics literature for those who want a deeper technical understanding. In addition, since auctions are an increasingly important topic in computer science, we also look at work on auctions from the computer science literature. Overall, our aim is to identifying what both these bodies of work these tell us about creating electronic auctions. © 2011 ACM. Source

Torra V.,Institute dInvestigacio en Intelligencia Artificial | Narukawa Y.,Toho Gakuen School of Music
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

Non-additive (fuzzy) measures also known as cooperative games or capacities are set functions that can be used to evaluate subsets of a reference set. In order to evaluate their similarities and differences, we can consider distances between pairs of measures. Games have been extended to communication situations in which besides of the game there is a graph that establishes which sets are feasible (which coalitions are possible, which individuals can cooperate). In this paper we consider the problem of defining a distance for pairs of measures when not all sets are feasible. © 2014 Springer International Publishing. Source

Torra V.,Institute dInvestigacio en Intelligencia Artificial
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

Privacy preserving data mining tools only use in a limited way information and knowledge other than the data base being protected. In this paper we plead on the need of knowledge intensive tools in data privacy. More especifically, we discuss the role of knowledge related tools in data protection and in disclosure risk assessment. © 2011 Springer-Verlag. Source

Garrigues C.,University of Barcelona | Robles S.,Autonomous University of Barcelona | Borrell J.,Autonomous University of Barcelona | Navarro-Arribas G.,Institute dInvestigacio en Intelligencia Artificial
Journal of Systems and Software | Year: 2010

In this paper, we present a software architecture and a development environment for the implementation of applications based on secure mobile agents. Recent breakthroughs in mobile agent security have unblocked this technology, but there is still one important issue to overcome: the complexity of programming applications using these security solutions. Our proposal aims to facilitate and speed up the process of implementing cryptographic protocols, and to allow the reuse of these protocols for the development of secure mobile agents. As a result, the proposed architecture and development environment promote the use of mobile agent technology for the implementation of secure distributed applications. © 2009 Elsevier Inc. All rights reserved. Source

Ladra S.,University of La Coruna | Torra V.,Institute dInvestigacio en Intelligencia Artificial
International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems | Year: 2010

Synthetic data generators are one of the methods used in privacy preserving data mining for ensuring the privacy of the individuals when their data are published. Synthetic data generators construct artificial data from some models obtained from the original data. Such models are mainly based on statistics and, typically, do not take into account other aspects of interest in artificial intelligence. In this paper we study whether one family of such synthetic data generators (the IPSO family) preserves the properties of the data that are of interest when users plan to apply clustering techniques. In particular, we study the effect of such synthetic data generators on fuzzy clustering. That is, we study the information loss data suffer when the original data are replaced by the synthetic ones. © 2010 World Scientific Publishing Company. Source

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