Institute dInvestigacio en Intelligencia Artificial

La Línea de la Concepción, Spain

Institute dInvestigacio en Intelligencia Artificial

La Línea de la Concepción, Spain
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Ferreira L.A.,Methodist University of Sao Paulo | C. Bianchi R.A.,State University of Maringa | Santos P.E.,State University of Maringa | de Mantaras R.L.,Institute Dinvestigacio En Intelligencia Artificial
Applied Intelligence | Year: 2017

Non-stationary domains, where unforeseen changes happen, present a challenge for agents to find an optimal policy for a sequential decision making problem. This work investigates a solution to this problem that combines Markov Decision Processes (MDP) and Reinforcement Learning (RL) with Answer Set Programming (ASP) in a method we call ASP(RL). In this method, Answer Set Programming is used to find the possible trajectories of an MDP, from where Reinforcement Learning is applied to learn the optimal policy of the problem. Results show that ASP(RL) is capable of efficiently finding the optimal solution of an MDP representing non-stationary domains. © 2017 Springer Science+Business Media New York

Andrighetto G.,National Research Council Italy | Andrighetto G.,University of Florence | Brandts J.,Autonomous University of Barcelona | Conte R.,National Research Council Italy | And 3 more authors.
PLoS ONE | Year: 2013

Material punishment has been suggested to play a key role in sustaining human cooperation. Experimental findings, however, show that inflicting mere material costs does not always increase cooperation and may even have detrimental effects. Indeed, ethnographic evidence suggests that the most typical punishing strategies in human ecologies (e.g., gossip, derision, blame and criticism) naturally combine normative information with material punishment. Using laboratory experiments with humans, we show that the interaction of norm communication and material punishment leads to higher and more stable cooperation at a lower cost for the group than when used separately. In this work, we argue and provide experimental evidence that successful human cooperation is the outcome of the interaction between instrumental decision-making and the norm psychology humans are provided with. Norm psychology is a cognitive machinery to detect and reason upon norms that is characterized by a salience mechanism devoted to track how much a norm is prominent within a group. We test our hypothesis both in the laboratory and with an agent-based model. The agent-based model incorporates fundamental aspects of norm psychology absent from previous work. The combination of these methods allows us to provide an explanation for the proximate mechanisms behind the observed cooperative behaviour. The consistency between the two sources of data supports our hypothesis that cooperation is a product of norm psychology solicited by norm-signalling and coercive devices. © 2013 Andrighetto et al.

Erola A.,Rovira i Virgili University | Castella-Roca J.,Rovira i Virgili University | Navarro-Arribas G.,Institute dInvestigacio en Intelligencia Artificial | 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: 2010

The publication of Web search logs is very useful for the scientific research community, but to preserve the users' privacy, logs have to be submitted to an anonymization process. Random query swapping is a common technique used to protect logs that provides k-anonymity to the users in exchange for loss of utility. With the assumption that by swapping queries semantically close this utility loss can be reduced, we introduce a novel protection method that semantically microaggregates the logs using the Open Directory Project. That is, we extend a common method used in statistical disclosure control to protect search logs from a semantic perspective. The method has been tested with a random subset of AOL search logs, and it has been observed that new logs improve the data usefulness. © 2010 Springer-Verlag Berlin Heidelberg.

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.

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.

Torra V.,Institute dInvestigacio en Intelligencia Artificial | Min J.-H.,Hanyang University
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

In a recent paper we introduced intuitionistic fuzzy partitions or interval-valued fuzzy partitions as a way to represent the uncertainty of fuzzy clustering. In this paper we reconsider these definitions so that these fuzzy partitions can be used to represent other uncertainties on the clustering processes. © 2010 Springer-Verlag.

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.

Bou F.,Institute dInvestigacio en Intelligencia Artificial
Proceedings of The International Symposium on Multiple-Valued Logic | Year: 2010

In this paper we axiomatize the formulas that, in the infinite-valued (standard) Łukasiewicz algebra, always take a value above certain fixed number. This generalizes the approach considered in the infinite-valued Łukasiewicz logic, where the fixed number is the maximum. © 2010 IEEE.

Juarez M.,Institute dInvestigacio en Intelligencia Artificial | Torra V.,Institute dInvestigacio en Intelligencia Artificial
International Journal of Intelligent Systems | Year: 2013

In this paper, we tackle the private information retrieval (PIR) problem associated with the use of Internet search engines. We address the desire for a user to retrieve information from the Web without the search provider learning about it. Traditional PIR protocols present two main shortcomings for their application: (i) They assume cooperation by the database, which is not affordable for a real-world search engine like Google and (ii) their computational complexity is linear in the size of the database, which is unfeasible in the case of the Web. More recent approaches relax PIR conditions to overcome these limitations and present some level of privacy. Mostly, they aim to distort server logs regardless of the loss of information that is involved. Server logs are used by search engines for profiling and, thereby, provide personalized results. This becomes a user's need given the growth of the Web and can also be used for targeted advertising. This study focuses on a noncooperative agent for private search that considers profiling as valuable data used for both sides of the search process. It is based on the assumption that the user's identity is formed by the union of various areas of interests or facets. Managing the HTTP connections properly, submitted queries are mapped to different server logs according to these facets. The rationale is that these logs cannot be used for tracing the user while they are still helpful for profiling. We present a personalized query classification approach based on the user's browsing history and to provide empirical results; we developed an attacking algorithm against the agent that shows that the disclosure risk is reduced. © 2013 Wiley Periodicals, Inc.

Ladra S.,University of La Coruña | 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.

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