کلمات کلیدی مربوط به کتاب سیستم های چند عاملی: مهندسی انفورماتیک و کامپیوتر، طراحی سیستم های اطلاعاتی
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Издательство InTech, 2009, -434 pp.
Multi agent systems involve a team of
agents working together socially to accomplish a task. An agent
can be social in many ways. One is when an agent helps others
in solving complex problems. The field of multi agent systems
investigates the process underlying distributed problem solving
and designs some protocols and mechanisms involved in this
process. This book presents an overview about some of the
research issues in the field of multi agents.
This book can be divided into 4 parts. The first part (Chapters
1-3) deals with resources distribution and sharing among
agents. Chapter 1 presents the allocation of resources in multi
agent societies. The objective function and available resources
are mathematically modelled and a discrete time representation
of the system is also presented. The objective is to cope with
resource allocations in dynamic environments. Chapter 2
presents an overview of the negotiation protocols in decision
making. A fuzzy constraint based model is presented, analyzed
and simulated for automated purchase negotiations. In order to
have a better allocation of resources, multi agents can be
equipped with negotiation attributes. Chapter 3 presents goal
oriented approach to dynamically model a system, which can be
used for process optimization and automation. The chapter
presents industry-proven BPMS employing goal-oriented approach
to modelling and executing business processes.
The second part (Chapter 4-5) deals with the modelling and
analysis of multi agent systems. Petri nets are graphical
modelling tools used to describe and analyse systems. In
chapter 4, the multi agent framework is modelled using Petri
nets. The Petri net model is obtained locally for each agent.
Furthermore, a combined global model is also obtained. The
global model is then analysed to study the properties of the
system. The liveness and boundedness properties in the Petri
net domain are analysed, which can give information about the
communication and interaction mechanism of the multi-agent
system. Chapter 5 presents a simulation framework, in which
Bluetooth piconet profile is used for communication. A state
space model of multi agent robots is also presented. The model
is used to design and simulate feedback control strategies for
trajectory tracking of the agents. A critical analysis of
nonlinear feedback and feedback linearized control strategies
is presented.
The third part (Chapter 6-13) deals with the coordination and
communication issues in multi agent systems. Chapter 6
investigates the coordination techniques used in semiconductor
manufacturing system, while maintaining the desired throughput.
The design of a process for enabling agent based computing is
presented in Chapter 7 . The service agents negotiate to select
a final solution via a negotiation process using service
quality and service payoff as the criteria. Chapter 8 focuses
on coordination control and fault diagnosis of production
system. The ways of agents’ information exchange and the
cooperation behaviour of agents are also presented. Chapter 9
deals with cooperation approaches using game theory. The
rational and selfish behaviour in agent societies in terms of
individual as well as collective activities is defined. Chapter
10 focuses on the indirect coordination mechanisms in multi
agents.
Multi agent bluffing is considered as an unexpected behaviour
and multi agents should be equipped to learn to predict its
opponents’ reactions based not only on its own cards, but on
the actions of those around it. Chapter 11 presents a
comprehensive overview about multi agent bluffing. One of the
important issues in multi agent coordination is the use of a
common language in multi agent societies. Chapter 12 presents a
language for coordination which is capable of describing agent
behaviour globally, locally and in a team. In certain
environments and applications, it is necessary to ensure secure
communication among agents. Of particular interest are wireless
networks, which are more vulnerable to threats. Chapter 13
presents an agent-oriented key distribution protocol for
wireless networks.
The fourth part (Chapter 14-20) deals with the design of
frameworks for different applications of multi agents. This
part also includes research papers which focus on the
applications of multi agent systems. A framework for process
simulation to support flexible activity scheduling is presented
in Chapter 14 . Social rationality is used to represent the
utility function. The decision making strategies along with
communication mechanism are also presented. Chapter 15 focuses
on the application of multi agents in production, economical
and social domains. The coalition formation for large scale
multi agent system is also presented. One of the objectives for
multi agent robotic systems is to track moving objects. Chapter
16 focuses on multi agents executing different tactics over the
tracked target and collaborating with the tracked target.
Chapter 17 presents scheduling system for multi agents, in
which machine agents and task agents interact to achieve
optimal or near-optimal global performances. The scheduling
system assumes the combination of meta-heuristics. Chapter 18
presents a new dimension for the applications of multi agents.
In this chapter, multi agents are employed as educational
agents, which allow instructive communication and interaction
between human characters. Chapter 19 focuses on the deployment
of multi agent systems in auction and electronic markets using
the Internet. Different types of transactions in electronic
markets are classified and accordingly mechanisms are designed
for the markets. Chapter 20 presents a multi agent architecture
for the transport multimodal information systems. The objective
is to optimize the composition of services in terms of cost and
total response delay.
In summary, this book presents a combination of different
research issues which are pursued by researchers in the domain
of multi agent systems. Multi agent systems are one of the best
ways to understand and model human societies and behaviours. In
fact, such systems are the systems of future.
Agent-Based Distributed Resource
Allocation in Continuous Dynamic Systems
Constraint Based Automated Multi-attribute Negotiations
Goal-Oriented Autonomic Business Process Modelling and
Execution
Modeling and Analysis Methods for Multi-agent Systems
Control Analysis and Feedback Techniques for Multi Agent
Robots
Scalable Coordination Mechanism to Maintain Throughput of
Dynamic Multiagent Networks
Requirements Driven Service Agent Collaboration
Coordination Control and Fault Diagnosis of Production System
Using Multi-agent Technology
Evolutionary Game Theory based Cooperation Algorithm in
Multi-agent System
Indirect Coordination Mechanism of MAS
A Multi-Agent Approach to Bluffing
MASL: a Language for Multi-Agent System
Agent-Oriented Novel Quantum Key Distribution Protocol for the
Security in Wireless Network
A Framework for Business Process Simulation Based on
Multi-Agent Cooperation
Agent Oriented Engineering and Methodologies with Application
to Production, Economical and Social Systems
Effective Multi-Model Motion Tracking Under Multiple Team
Member Actuators
MASDScheGATS - Scheduling System for Dynamic Manufacturing
Environmemts
Conversational Characters that Support Interactive Play and
Learning for Children
Auctions and Electronic Markets
Distributed Optimisation using the Mobile Agent Paradigm
through an Adaptable Ontology: Multi-operator Services Research
and Composition