Multi‐agent technologies in economics

• Published date: 01 April 2017
• Author: Javier Bajo,María José Escalona,Philippe Mathieu
• Date: 01 April 2017
• DOI: http://doi.org/10.1002/isaf.1415

SPECIAL ISSUE ARTICLE

Multi‐agent technologies in economics

Javier Bajo

1

|Philippe Mathieu

2

|María José Escalona

3

1

Departamento de Inteligencia Artificial,

Universidad Politécnica de Madrid, Madrid,

Spain

2

Université de Lille, Villeneuve‐d'Ascq, France

3

ETS Ingeniería Informática, Universidad de

Sevilla, Seville, Spain

Correspondence

Javier Bajo, Departamento de Inteligencia

Artificial, Universidad Politécnica de Madrid,

Madrid, Spain.

Email: jbajo@fi.upm.es

Summary

This paper summarizes some of the trends in the use of multi‐agent technologies in economics.

Multiple agent systems, fuzzy sets and neural networks are critical tools used to investigate the

emerging economics research agenda related to data mining, dynamic markets stock selection

and bank stress testing. This paper reviews the contributions of four such examples.

KEYWORDS

distributed systems, economics, intelligent systems,multi‐agent systems

Increasingly, applications in economics, finance and markets are using

tools based on artificial intelligence, including multi‐agent systems,

fuzzy sets, genetic algorithms, neural networks and other approaches,

in order to garner a better understanding of the emerging issues.

Issues such as the interaction of different markets (e.g. Widiputra,

Pears, Serguieva, & Kasabov, 2009), the automation of explanations

(e.g. Daniels & Caron, 2009) and risk analysis (e.g. Ballini, Mendonça,

& Gomide, 2009; Canedo & Jaramillo, 2009) can require multiple

tools in order to capture the phenomena. Further, it is becoming

increasingly important for research to cross disciplinary boundaries

in order to access emerging research.

This issue of Intelligent Systems in Accounting, Finance and Manage-

ment presents a special issue based on papers from the International

Conference on Practical Applications on Agents and Multi‐Agent Sys-

tems (PAAMS 2016) held in Salamanca, Spain, 1–3 June 2016. PAAMS

provides an international forum to present and discuss the latest scien-

tific developments and their effective applications, to assess the

impact of the approach, and to facilitate technology transfer. PAAMS

started as a local initiative, but it has since grown to become the inter-

national yearly platform to present, to discuss and to disseminate the

latest developments and the most important outcomes related to

real‐world applications. It provides a unique opportunity to bring

multidisciplinary experts, academics and practitioners together to

exchange their experience in the development and deployment of

agents and multi‐agent systems. PAAMS intends to bring together

researchers and developers from industry and the academic world to

report on the latest scientific and technical advances on the application

of multi‐agent systems, to discuss and debate the major issues, and to

showcase the latest systems using agent‐based technology. It will

promote a forum for discussion on how agent‐based techniques,

methods and tools help system designers to accomplish the mapping

between available agent technology and application needs. Other

stakeholders should be rewarded with a better understanding of the

potential and challenges of the agent‐oriented approach.

The conference is organized by the Bioinformatics, Intelligent

System and Educational Technology Research Group (http://bisite.

usal.es/) of the University of Salamanca. During recent years, artificial

intelligence systems applied to accounting, financing and management

have gained relevance (Albanis & Batchelor, 2007; Almejalli, Dahal, &

Hossain, 2007; Aragonés, Blanco, & Estévez, 2007; Ballini et al.,

2009; Canedo & Jaramillo, 2009; Daniels & Caron, 2009; Di Napoli,

Santamaria, & Rossi, 2017; Galeshchuk, 2017). This special issue is

based on selected, expanded and significantly revised versions of the

best papers presented at the conference focused on distributed

artificial intelligence systems in accounting and financing.

In the first paper, Di Napoli et al. (2017) present a decision support

system aimed at helping involved stakeholders to make decisions to

plan passengers' transportation in the city and also to evaluate the

consequences for the city if the plans are really implemented. Cruise

tourism represents a strategic sector for the economic growth of

several countries impacting on different direct and indirect markets.

The arrival of cruises in a city represents an unmissable opportunity

to increment its tourist market penetration. The proposed system is

designed according to the multi‐agent paradigm, allowing one to easily

manage the necessary coordination among different entities and data

sources that are usually distributed and need to cooperate to provide

useful suggestions. In addition, a prototype of a web‐based application

is provided to end users, so that it can run on heterogeneous plat-

forms, and it can be easily accessed by different users from different

devices, as is the case for the application domain considered. The

novelty of the approach proposed in this work is to adopt a system

design methodology that allows one to clearly separate the different

DOI: 10.1002/isaf.1415

Intell Sys Acc Fin Mgmt. 2017;24:59–61. Copyright © 2017 John Wiley & Sons, Ltd.wileyonlinelibrary.com/journal/isaf 59