FuzzyOrganization of Self-Adaptive Agents Based On Software Components

2014 ◽  
Vol 10 (3) ◽  
pp. 36-56 ◽  
Author(s):  
Abderrahim Siam ◽  
Ramdane Maamri ◽  
Zaïdi Sahnoun
Keyword(s):  
Membership Function ◽  
Software Components ◽  
Automatic Assembly ◽  
Multi Agent Systems ◽  
Adaptive Agents ◽  
Agent Systems ◽  
Proposed Model ◽  
Multi Agent ◽  
The Membership Function ◽  
Self Adaptive

This paper addresses the development of organizational multi agent systems as a preferred solution to develop open, distributed and adaptive application. It proposes a combination between components and agents to define a flexible organizational model of MAS based on three concepts: roles, self-adaptive agents based on components and fuzzy groups. Roles are played by agents in fuzzy groups. A fuzzy group is a fuzzy set of agents characterized by a membership function expressing the partial membership of each agent to the group. The membership function expresses the degree of capacity of each agent to play a role. This work proposes a fuzzy measure of the capacity of agents to play roles. It proposes a model of auto adaptive agents constructed by automatic assembly (reassembly) of software components. Components implement required capabilities to play roles. The proposed model and introduced concepts have been tested using the Madkit platform.

How Can We Trust Agents in Multi-Agent Environments? Techniques and Challenges

2009 ◽  
pp. 2843-2864 ◽  
Author(s):  
Kostas Kolomvatsos ◽  
Stathes Hadjiefthymiades
Keyword(s):  
Computer Science ◽  
Research Area ◽  
Software Components ◽  
Important Research ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Potential Partner ◽  
Multi Agent ◽  
Important Research Area

The field of Multi-agent systems (MAS) has been an active area for many years due to the importance that agents have to many disciplines of research in computer science. MAS are open and dynamic systems where a number of autonomous software components, called agents, communicate and cooperate in order to achieve their goals. In such systems, trust plays an important role. There must be a way for an agent to make sure that it can trust another entity, which is a potential partner. Without trust, agents cannot cooperate effectively and without cooperation they cannot fulfill their goals. Many times, trust is based on reputation. It is an indication that we may trust someone. This important research area is investigated in this book chapter. We discuss main issues concerning reputation and trust in MAS. We present research efforts and give formalizations useful for understanding the two concepts.

scholarly journals Self-Adaptive Swarm System (SASS)

2021 ◽  
Author(s):  
Qin Yang
Keyword(s):  
Artificial Intelligence ◽  
Distributed Artificial Intelligence ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Collective Decisions ◽  
Fourth Level ◽  
Working Together ◽  
Multi Agent ◽  
Communication Planning ◽  
Self Adaptive

Distributed artificial intelligence (DAI) studies artificial intelligence entities working together to reason, plan, solve problems, organize behaviors and strategies, make collective decisions and learn. This Ph.D. research proposes a principled Multi-Agent Systems (MAS) cooperation framework -- Self-Adaptive Swarm System (SASS) -- to bridge the fourth level automation gap between perception, communication, planning, execution, decision-making, and learning.

R2-IBN

2009 ◽  
pp. 144-157
Author(s):  
Lobna Hsairi ◽  
Khaled Ghédira ◽  
Adel M. Alim ◽  
Abdellatif BenAbdelhafid
Keyword(s):  
Information Management ◽  
Organizational Structures ◽  
Agent Technology ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Intelligent Software ◽  
Proposed Model ◽  
Multi Agent ◽  
Collaboration And Communication ◽  
Negotiation Problem

In the age of information proliferation, openness, open information management, interconnectivity, collaboration and communication advances, extended enterprises must be up to date to the new strategic, economic and organizational structures. Consequently, intelligent software based on agent technology emerges to improve system design, and to increase enterprise competitive position as well. The competitiveness is based on the information management, cooperation, collaboration and interconnectivity. Thus, within these interconnectivity and cooperation, conflicts may arise. The automated negotiation plays a key role to look for a common agreement. Argumentation theory has become an important topic in the field of Multi-Agent Systems and especially in the negotiation problem. In this chapter, first, the proposed model MAIS-E2 (Multi-Agent Information System for an Extended Enterprise) is presented. Then an argumentation based negotiation framework: Relationship-Role and Interest Based Negotiation (R2-IBN) framework is presented, and within this framework, the authors focused mainly on, argument generation module via inference rules and argument selection module via fuzzy logic.

A multi-agent systems-based contractor pre-qualification model

2016 ◽  
Vol 23 (6) ◽  
pp. 709-726 ◽  
Author(s):  
Faikcan Kog ◽  
Hakan Yaman
Keyword(s):  
Selection Process ◽  
Construction Sector ◽  
Multi Agent Systems ◽  
Content Type ◽  
Quantitative Survey ◽  
Agent Systems ◽  
Proposed Model ◽  
Multi Agent ◽  
User Friendly ◽  
Selection Of

Purpose The selection of the contractor, as a main participant of a construction project, is the most important and challenging decision process for a client. The purpose of this paper is to propose a multi-agent systems (MAS)-based contractor pre-qualification (CP) model for the construction sector in the frame of the tender management system. Design/methodology/approach The meta-classification and analysis study of the existing literature on CP, contractor selection and criteria weighting issues, which examines the current and important CP criteria, other than price, is introduced structurally. A quantitative survey, which is carried out to estimate initial weightings of the identified criteria, is overviewed. MAS are used to model the pre-qualification process and workflows are shown in Petri nets formalism. A user-friendly prototype program is created in order to simulate the tendering process. In addition, a real case regarding the construction work in Turkey is analyzed. Findings There is a lack of non-human-driven solutions and automation in CP and in the selection problem. The proposed model simulates the pre-qualification process and provides consistent results. Research limitations/implications The meta-classification study consists of only peer-reviewed papers between 1992 and 2013 and the quantitative survey initiates the perspectives of the actors of Turkish construction sector. Only the traditional project delivery method is selected for the proposed model, that is other delivery methods such as design/build, project management, etc., are not considered. Open, selective limited and negotiated tendering processes are examined in the study and the direct supply is not considered in the scope. Practical implications The implications will help to provide an objective CP and selection process and to prevent the delays, costs and other troubles, which are caused by the false selection of a contractor. Originality/value Automation and simulation in the pre-qualification and the selection of the contractor with a non-human-driven intelligent solution ease the decision processes of clients in terms of cost, time and quality.

Sign in / Sign up

Export Citation Format

Share Document