Towards a New Approach for Modelling Interactive Real Time Systems Based on Collaborative Decisions Network

Network Protocols and Algorithms

Jaime Lloret³  Mostafa Ezziyyani¹  Soumaya EL Mamoune² 

[1] ABDELMALEK ESSAADI University;Polytechnic University of Valencia

关键词: Adaptive system;    auto-improvement;    collaborative system;    decision-making;    graph of decision;    interaction with the environment;    modeling of the behavior;    network of decision;   

DOI  :  10.5296/npa.v7i1.7257

学科分类：计算机应用

来源: Macrothink Institute, Inc.

【 摘 要 】

Adaptive systems are being used in many research fields such as e-Learning, switching in the telephone network and for organizing contents on the Web. Each field requires a particular adaptation system which is not generally applicable to the other contexts. The lack of several criteria like the interaction with the environment, the self-improvement and the evaluation pushed us to look further and suggest a generalized solution for any context. In this article, we present a new approach for the adaptation of the interactive systems of decision-making to offer suitable services to a given situation based on the interaction with the environment, the auto-improvement and the evolution of the system. The approach suggested is a graphic modelling called decisions network which will serve the design and construction of the dynamic operation of the core of the adaptive systems of decision-making. The service offered by such system is an adaptive final decision of the core which is a result got by the combination of the nodes of the decisions network and its iterative interactions via the environmental data. This work has two objectives: on the one hand, to present the new approach with its components and its importance by reporting existing work and, on the other hand, to present the approach with the chart and the formalization in order to model the dynamic behavior of the system via the search for a final decision in the form of adjacent elementary decisions.

【 授权许可】

Unknown