A multiagent architecture for fuzzy modeling

Delgado, Miguel; Gmez-Skarmeta, A. F.; Marn-Blzquez, J. Gmez; Barber, Heather

doi:10.1002/(sici)1098-111x(199903)14:3<305::aid-int5>3.0.co;2-p

Cited by 9 publications

(2 citation statements)

References 21 publications

(16 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several proposals about intelligent software agents have been emerging in the recent last years, but the lack of connection, communication and consensus among them have lead to a decrease in the quality and suitability of the retrieved information besides the efficiency of the system in the recovering and filtering task. This fact keeps the need of proposals in the field, and emphasizes the importance of the design and development of intelligent software agent organisations, as well as hierarchies and architectures that hold up such structures [7,10,21,28,29].However, not only is needed some organization, but also a protocol of communication among the agents. The great variety of representations and evaluations of the information in the Internet is the main obstacle to this communication, and the problem becomes more noticeable when the user takes part in the process.…”

mentioning

confidence: 99%

A communication model based on the 2-tuple fuzzy linguistic representation for a distributed intelligent agent system on Internet

Delgado

Herrera

Herrera‐Viedma

et al. 2002

Soft Computing - A Fusion of Foundations, Methodologies and App

Self Cite

View full text Add to dashboard Cite

Internet users are assisted by means of distributed intelligent agents in the information gathering process to find the fittest information to their needs. In this paper we present a distributed intelligent agent model where the communication of the evaluation of the retrieved information among the agents is carried out by using linguistic operators based on the 2-tuple fuzzy linguistic representation as a way to endow the retrieval process with a higher flexibility, uniformity and precision. The 2-tuple fuzzy linguistic representation model allows to make processes of computing with words without loss of information. IntroductionIn the framework of the information retrieval one of the most current problems nowadays for which the fuzzy linguistic approach may be very useful, is the retrieval, handling and identification of relevant information through the Internet.The fuzzy linguistic approach is an approximate technique, which represents qualitative aspects as linguistic values by means of linguistic variables, that is, variables whose values are not numbers but words or sentences in a natural or artificial language [36]. This approach has been applied successfully to different areas as economics [14,31], planning [1], decision-making [12, 32], information retrieval [3,9,18,19], etc.Intelligent agents [4,11,26,29,34] deal with the information gathering process assisting the Internet users to find the fittest information to their needs. Several proposals about intelligent software agents have been emerging in the recent last years, but the lack of connection, communication and consensus among them have lead to a decrease in the quality and suitability of the retrieved information besides the efficiency of the system in the recovering and filtering task. This fact keeps the need of proposals in the field, and emphasizes the importance of the design and development of intelligent software agent organisations, as well as hierarchies and architectures that hold up such structures [7,10,21,28,29].However, not only is needed some organization, but also a protocol of communication among the agents. The great variety of representations and evaluations of the information in the Internet is the main obstacle to this communication, and the problem becomes more noticeable when the user takes part in the process. The complexity of all these processes reveals the need of more flexibility in the communication among agents and between agents and the user [9,34,35]. For this purpose, several approaches related to mechanisms to introduce and handle flexible information through linguistic labels have been proposed both at levels of agents and users [8,33].The main drawback of these approaches is the lack of precision in the final results, due to the fact that appears a loss of information in the processes of computing with words (CW). To overcome this drawback in [15] was presented a linguistic computational model based on linguistic 2-tuples which provides a computational technique to deal with linguistic information in a precise ...

show abstract

mentioning

confidence: 99%

A communication model based on the 2-tuple fuzzy linguistic representation for a distributed intelligent agent system on Internet

Delgado

Herrera

Herrera‐Viedma

et al. 2002

Soft Computing - A Fusion of Foundations, Methodologies and App

Self Cite

View full text Add to dashboard Cite

show abstract

“…The possibility of their application to the modelling and study of stock market phenomena was demonstrated on a simple example of a central agency that regulates the behaviour of the investors. Delgado et al (1999) investigated a hybrid learning system that combines different fuzzy modelling techniques. In order to implement the different methods, they proposed the use of intelligent agents, which collaborate by means of a multi-agent architecture.…”

Section: Introductionmentioning

confidence: 99%

Information and knowledge exchange in a multi-agent system for stock trading

Luo

Davis²,

Liu³

2001 Enterprise Networking, Applications and Services Conference Proceedings.. EntNet@SUPERCOMM2001 (Cat. No.01EX543)

View full text Add to dashboard Cite

A distributed problem solving system can be characterised as a group of individual agents running and co-operating with other agents to solve a problem. As dynamic domains such as stock trading are continuing to grow in complexity, it becomes more difficult to control the behaviour of agents in the domains where unexpected events can occur. This paper presented an information and knowledge exchange framework to support the distributed problem solving in the stock trading domain. It addresses two important issues: (1) How individual agents should be interconnected so that their capacities are efficiently used and their goals are accomplished effectively and efficiently; (2) How the information and knowledge transfer should take place among agents to allow them to respond successfully to user requests and unexpected situations in the outside world. The focus of this paper is dynamic knowledge exchange among MASST agents. The co-ordinator agent together with a decision enabling warehouse acting as a dynamic blackboard plus direct intercommunication among the agents enable facts, commands, and rules to be transferred between MASST agents. Knowledge can be exchanged among the agents by using a combination of facts, rules and commands transfers.

show abstract