Juan A. Rodríguez-Aguilar

Bio: Juan A. Rodríguez-Aguilar is an academic researcher from Spanish National Research Council. The author has contributed to research in topics: Multi-agent system & Combinatorial auction. The author has an hindex of 36, co-authored 233 publications receiving 5065 citations. Previous affiliations of Juan A. Rodríguez-Aguilar include Massachusetts Institute of Technology & Autonomous University of Barcelona.

Issues in multiagent resource allocation

Abstract: Issues in Multiagent Resource Allocation Yann Chevaleyre, Paul E. Dunne, Ulle Endriss, Jerome Lang, Michel Lemaitre, Nicolas Maudet, Julian Padget, Steve Phelps, Juan A. Rodrigues-Aguilar, Paulo Sousa Abstract: The allocation of resources within a system of autonomous agents, that not only have preferences over alternative allocations of resources but also actively participate in computing an allocation, is an exciting area of research at the interface of Computer Science and Economics. This paper is a survey of some of the most salient issues in Multiagent Resource Allocation. In particular, we review various languages to represent the preferences of agents over alternative allocations of resources as well as different measures of social welfare to assess the overall quality of an allocation. We also discuss pertinent issues regarding allocation procedures and present important complexity results. Our presentation of theoretical issues is complemented by a discussion of software packages for the simulation of agent-based market places. We also introduce four major application areas for Multiagent Resource Allocation, namely industrial procurement, sharing of satellite resources, manufacturing control, and grid computing.

AMELI: An Agent-Based Middleware for Electronic Institutions

Abstract: The design and development of open multi-agent systems (MAS) is a key aspect in agent research. We advocate that they can be realised as electronic institutions. In this paper we focus on the execution of electronic institutions by introducing AMELI, an infrastructure that mediates agentsý interactions while enforcing institutional rules. An innovative feature of AMELI is that it is of general purpose (it can interpret any institution specification), and therefore it can be regarded as domain-independent. The combination of ISLANDER [5] and AMELI provides full support for the design and development of electronic institutions.

On the formal specification of electronic institutions

Abstract: In this article we argue that open agent organisations can be effectively designed and implemented as institutionalized electronic organisations ('electronic institutions') composed of a vast amount of heterogeneous (human and software) agents playing different roles and interacting by means of speech acts. Here we take the view that the desing and development of electronic institutions must be guided by a principled methodology. Along this direction, we advocate for the presence of an underlying formal method that underpins the use of structured design techniques and formal analysis, facilitating development, composition and reuse. For this purpose we propose a specification formalism for electronic institutions that found their design, analysis and development. Source URL: https://www.iiia.csic.es/en/node/54893 Links [1] https://www.iiia.csic.es/en/staff/marc-esteva [2] https://www.iiia.csic.es/en/staff/juan-rodr%C3%ADguez-aguilar [3] https://www.iiia.csic.es/en/staff/carles-sierra [4] https://www.iiia.csic.es/en/staff/pere-garc%C3%ADa [5] https://www.iiia.csic.es/en/staff/josep-lluis-arcos [6] https://www.iiia.csic.es/en/bibliography?f[author]=485 [7] https://www.iiia.csic.es/en/bibliography?f[author]=2504

On the Formal Specifications of Electronic Institutions

Abstract: In this article we argue that open agent organisations can be effectively designed and implemented as institutionalized electronic organisations (electronic institutions) composed of a vast amount of heterogeneous (human and software) agents playing different roles and interacting by means of speech acts. Here we take the view that the design and development of electronic institutions must be guided by a principled methodology. Along this direction, we advocate for the presence of an underlying formal method that underpins the use of structured design techniques and formal analysis, facilitating development, composition and reuse. For this purpose we propose a specification formalism for electronic institutions that founds their design, analysis and development.

Auctions and bidding: A guide for computer scientists

Abstract: 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.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Phd by thesis

Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These