A Multi-Agent Smart E-Market Design at Work for Shariah Compliant Islamic Banking
Though quite fast on growth, Islamic financing at large, and its diverse instruments, is a controversial matter among scholars. This is evident from the ongoing debates on its Shariah compliance. Arguments, however, are inciting doubts and concerns among clients about its credibility, which is harming this lucrative sector. The work here investigates, particularly, some issues related to the Tawarruq instrument. The work examines the issues of linking Murabaha and Wakala contracts, the reselling of commodities to same traders, and the transfer of ownerships. The work affirms that a multi-agent smart electronic market design would facilitate Shariah compliance. The smart market exploits the rational decision-making capabilities of autonomous proxy agents that enable the clients, traders, brokers, and the bank buy and sell commodities, and manage transactions and cash flow. The smart electronic market design delivers desirable qualities that terminate the need for Wakala contracts and the reselling of commodities to the same traders. It also resolves the ownership transfer issues by allowing stakeholders to trade independently. The bank administers the smart electronic market and assures reliability of trades, transactions and cash flow. A multi-agent simulation is presented to validate the concept and processes. We anticipate that the multi-agent smart electronic market design would deliver Shariah compliance of personal financing to the aspiration of scholars, banks, traders and potential clients.
Consensus of Multi-Agent Systems under the Special Consensus Protocols
Two consensus problems are considered in this
paper. One is the consensus of linear multi-agent systems with
weakly connected directed communication topology. The other
is the consensus of nonlinear multi-agent systems with strongly
connected directed communication topology. For the first problem,
a simplified consensus protocol is designed: Each child agent can
only communicate with one of its neighbors. That is, the real
communication topology is a directed spanning tree of the original
communication topology and without any cycles. Then, the necessary
and sufficient condition is put forward to the multi-agent systems can
be reached consensus. It is worth noting that the given conditions do
not need any eigenvalue of the corresponding Laplacian matrix of the
original directed communication network. For the second problem,
the feedback gain is designed in the nonlinear consensus protocol.
Then, the sufficient condition is proposed such that the systems can
be achieved consensus. Besides, the consensus interval is introduced
and analyzed to solve the consensus problem. Finally, two numerical
simulations are included to verify the theoretical analysis.
Towards a Simulation Model to Ensure the Availability of Machines in Maintenance Activities
The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.
Edge Detection Using Multi-Agent System: Evaluation on Synthetic and Medical MR Images
Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.
An Architectural Model of Multi-Agent Systems for Student Evaluation in Collaborative Game Software
The teaching of computer programming for beginners
has been generally considered as a difficult and challenging task.
Several methodologies and research tools have been developed,
however, the difficulty of teaching still remains. Our work integrates
the state of the art in teaching programming with game software and
further provides metrics for the evaluation of student performance in
a collaborative activity of playing games. This paper aims to present a
multi-agent system architecture to be incorporated to the educational
collaborative game software for teaching programming that monitors,
evaluates and encourages collaboration by the participants. A
literature review has been made on the concepts of Collaborative
Learning, Multi-agents systems, collaborative games and techniques
to teach programming using these concepts simultaneously.
Agent-Based Simulation for Supply Chain Transport Corridors
Supply chains are the backbone of trade and
commerce. Their logistics use different transport corridors on regular
basis for operational purpose. The international supply chain
transport corridors include different infrastructure elements (e.g.
weighbridge, package handling equipments, border clearance
authorities, and so on). This paper presents the use of multi-agent
systems (MAS) to model and simulate some aspects of transportation
corridors, and in particular the area of weighbridge resource
optimization for operational profit. An underlying multi-agent model
provides a means of modeling the relationships among stakeholders
in order to enable coordination in a transport corridor environment.
Simulations of the costs of container unloading, reloading, and
waiting time for queuing up tracks have been carried out using data
sets. Results of the simulation provide the potential guidance in
making decisions about optimal service resource allocation in a trade
Intelligent Swarm-Finding in Formation Control of Multi-Robots to Track a Moving Target
This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbors are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.
Collaboration of Multi-Agent and Hyper-Heuristics Systems for Production Scheduling Problem
This paper introduces a framework based on the collaboration of multi agent and hyper-heuristics to find a solution of the real single machine production problem. There are many techniques used to solve this problem. Each of it has its own advantages and disadvantages. By the collaboration of multi agent system and hyper-heuristics, we can get more optimal solution. The hyper-heuristics approach operates on a search space of heuristics rather than directly on a search space of solutions. The proposed framework consists of some agents, i.e. problem agent, trainer agent, algorithm agent (GPHH, GAHH, and SAHH), optimizer agent, and solver agent. Some low level heuristics used in this paper are MRT, SPT, LPT, EDD, LDD, and MON
Multi-Agents Coordination Model in Inter- Organizational Workflow: Applying in Egovernment
Inter-organizational Workflow (IOW) is commonly
used to support the collaboration between heterogeneous and
distributed business processes of different autonomous organizations
in order to achieve a common goal. E-government is considered as an
application field of IOW. The coordination of the different
organizations is the fundamental problem in IOW and remains the
major cause of failure in e-government projects. In this paper, we
introduce a new coordination model for IOW that improves the
collaboration between government administrations and that respects
IOW requirements applied to e-government. For this purpose, we
adopt a Multi-Agent approach, which deals more easily with interorganizational
digital government characteristics: distribution,
heterogeneity and autonomy. Our model integrates also different
technologies to deal with the semantic and technologic
interoperability. Moreover, it conserves the existing systems of
government administrations by offering a distributed coordination
based on interfaces communication. This is especially applied in
developing countries, where administrations are not necessary
equipped with workflow systems. The use of our coordination
techniques allows an easier migration for an e-government solution
and with a lower cost. To illustrate the applicability of the proposed
model, we present a case study of an identity card creation in Tunisia.
Leader-following Consensus Criterion for Multi-agent Systems with Probabilistic Self-delay
This paper proposes a delay-dependent leader-following consensus condition of multi-agent systems with both communication delay and probabilistic self-delay. The proposed methods employ a suitable piecewise Lyapunov-Krasovskii functional and the average dwell time approach. New consensus criterion for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical example showed that the proposed method is effective.
A Preference-Based Multi-Agent Data Mining Framework for Social Network Service Users' Decision Making
Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.
Hybridized Technique to Analyze Workstress
Related Data via the StressCafé
This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to
fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach)
has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a
superior hybrid solution. Recent researches have shown that there is a
need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this
instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent
systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.
Interdisciplinary Principles of Field-Like Coordination in the Case of Self-Organized Social Systems1
This interdisciplinary research aims to distinguish universal scale-free and field-like fundamental principles of selforganization observable across many disciplines like computer science, neuroscience, microbiology, social science, etc. Based on these universal principles we provide basic premises and postulates for designing holistic social simulation models. We also introduce pervasive information field (PIF) concept, which serves as a simulation media for contextual information storage, dynamic distribution and organization in social complex networks. PIF concept specifically is targeted for field-like uncoupled and indirect interactions among social agents capable of affecting and perceiving broadcasted contextual information. Proposed approach is expressive enough to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. This paper gives some prospective vision how system-s resources (tangible and intangible) could be simulated as oscillating processes immersed in the all pervasive information field.
A Finite-Time Consensus Protocol of the Multi-Agent Systems
According to conjugate gradient algorithm, a new consensus protocol algorithm of discrete-time multi-agent systems is presented, which can achieve finite-time consensus. Finally, a numerical example is given to illustrate our theoretical result.
Trust Managementfor Pervasive Computing Environments
Trust is essential for further and wider acceptance of
contemporary e-services. It was first addressed almost thirty years
ago in Trusted Computer System Evaluation Criteria standard by
the US DoD. But this and other proposed approaches of that
period were actually solving security. Roughly some ten years ago,
methodologies followed that addressed trust phenomenon at its core,
and they were based on Bayesian statistics and its derivatives, while
some approaches were based on game theory. However, trust is a
manifestation of judgment and reasoning processes. It has to be dealt
with in accordance with this fact and adequately supported in cyber
environment. On the basis of the results in the field of psychology
and our own findings, a methodology called qualitative algebra has
been developed, which deals with so far overlooked elements of trust
phenomenon. It complements existing methodologies and provides a
basis for a practical technical solution that supports management of
trust in contemporary computing environments. Such solution is also
presented at the end of this paper.
Multi-Agent Systems Applied in the Modeling and Simulation of Biological Problems: A Case Study in Protein Folding
Multi-agent system approach has proven to be an effective and appropriate abstraction level to construct whole models of a diversity of biological problems, integrating aspects which can be found both in "micro" and "macro" approaches when modeling this type of phenomena. Taking into account these considerations, this paper presents the important computational characteristics to be gathered into a novel bioinformatics framework built upon a multiagent architecture. The version of the tool presented herein allows studying and exploring complex problems belonging principally to structural biology, such as protein folding. The bioinformatics framework is used as a virtual laboratory to explore a minimalist model of protein folding as a test case. In order to show the laboratory concept of the platform as well as its flexibility and adaptability, we studied the folding of two particular sequences, one of 45-mer and another of 64-mer, both described by an HP model (only hydrophobic and polar residues) and coarse grained 2D-square lattice. According to the discussion section of this piece of work, these two sequences were chosen as breaking points towards the platform, in order to determine the tools to be created or improved in such a way to overcome the needs of a particular computation and analysis of a given tough sequence. The backwards philosophy herein is that the continuous studying of sequences provides itself important points to be added into the platform, to any time improve its efficiency, as is demonstrated herein.
Exploring Dimensionality, Systematic Mutations and Number of Contacts in Simple HP ab-initio Protein Folding Using a Blackboard-based Agent Platform
A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
Evolutionary Query Optimization for Heterogeneous Distributed Database Systems
Due to new distributed database applications such as
huge deductive database systems, the search complexity is constantly
increasing and we need better algorithms to speedup traditional
relational database queries. An optimal dynamic programming
method for such high dimensional queries has the big disadvantage of
its exponential order and thus we are interested in semi-optimal but
faster approaches. In this work we present a multi-agent based
mechanism to meet this demand and also compare the result with
some commonly used query optimization algorithms.
An Agent Oriented Approach to Operational Profile Management
Software reliability, defined as the probability of a
software system or application functioning without failure or errors
over a defined period of time, has been an important area of research
for over three decades. Several research efforts aimed at developing
models to improve reliability are currently underway. One of the
most popular approaches to software reliability adopted by some of
these research efforts involves the use of operational profiles to
predict how software applications will be used. Operational profiles
are a quantification of usage patterns for a software application. The
research presented in this paper investigates an innovative multiagent
framework for automatic creation and management of
operational profiles for generic distributed systems after their release
into the market. The architecture of the proposed Operational Profile
MAS (Multi-Agent System) is presented along with detailed
descriptions of the various models arrived at following the analysis
and design phases of the proposed system. The operational profile in
this paper is extended to comprise seven different profiles. Further,
the criticality of operations is defined using a new composed metrics
in order to organize the testing process as well as to decrease the time
and cost involved in this process. A prototype implementation of the
proposed MAS is included as proof-of-concept and the framework is
considered as a step towards making distributed systems intelligent
Designing a Football Team of Robots from Beginning to End
The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.
Simulation of Online Communities Using MAS Social and Spatial Organisations
Online Communities are an example of sociallyaware,
self-organising, complex adaptive computing systems.
The multi-agent systems (MAS) paradigm coordinated by
self-organisation mechanisms has been used as an effective
way for the simulation and modeling of such systems. In this
paper, we propose a model for simulating an online health
community using a situated multi-agent system approach,
governed by the co-evolution of the social and spatial
organisations of the agents.
Multi-agent Data Fusion Architecture for Intelligent Web Information Retrieval
In this paper we propose a multi-agent architecture for web information retrieval using fuzzy logic based result fusion mechanism. The model is designed in JADE framework and takes advantage of JXTA agent communication method to allow agent communication through firewalls and network address translators. This approach enables developers to build and deploy P2P applications through a unified medium to manage agent-based document retrieval from multiple sources.
An Agent-Based Approach to Vehicle Routing Problem
The paper proposes and validates a new method of solving instances of the vehicle routing problem (VRP). The approach is based on a multiple agent system paradigm. The paper contains the VRP formulation, an overview of the multiple agent environment used and a description of the proposed implementation. The approach is validated experimentally. The experiment plan and the discussion of experiment results follow.