Ahmed S., Karsiti M.N. (eds.) Multiagent Systems

Ahmed S., Karsiti M.N. (eds.) Multiagent Systems
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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

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