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

Abstract

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 ...

Incorporating filtering techniques in a fuzzy linguistic multi-agent model for information gathering on the web

“…It is developed from the multi-agent model deÿned in [6]. We propose to improve the performance of that by incorporating in its architecture both content-based ÿltering and collaborative ÿltering techniques.…”

“…This model develops the retrieval activity by considering ÿve action levels: internet users, interface agents, task agents, information agents and information sources. Using this model, in [6] we deÿned a fuzzy linguistic distributed multi-agent model that uses linguistic 2-tuples to carry out the communication processes among the agents. In such a way, we incorporate in the retrieval process a higher degree of exibility to carry out the information interchange, but in a precise way.…”

“…Then, our idea consists of applying the use of recommender systems in the multi-agent model presented in [6] to improve its performance. The incorporation of recommender systems in its architecture increases its information ÿltering possibilities on the Web.…”

“…This reveals the need of more exibility in the communication among agents and between agents and users [7,[31][32][33]. To solve this problem we presented in [6,7,12] di erent distributed intelligent agent models based on fuzzy linguistic information. Using di erent fuzzy linguistic approaches [13,14,34], in [6,7,12] we proposed to introduce and handle exible information by means of linguistic labels, and in such a way, improving communication processes.…”

“…We design it by using a 2-tuple fuzzy linguistic approach [14,15] as a way to endow the retrieval process with a higher exibility, uniformity and precision. As we did in [6], the communication of the evaluation of the retrieved information among the agents is carried out by using linguistic information represented by the 2-tuple fuzzy linguistic representation. The main novelty of this multi-agent model is that it combines both content-based ÿltering and collaborative ÿltering techniques.…”