Formal Modelling of the Dynamic Behaviour of Biology-Inspired, Agent-Based Systems

Formal Modelling of the Dynamic Behaviour of Biology-Inspired, Agent-Based Systems

Petros Kefalas (CITY College, Thessaloniki, Greece), G. Eleftherakis (CITY College, Thessaloniki, Greece) and I. Stamatopoulou (University of Sheffield, UK)
Copyright: © 2005 |Pages: 34
DOI: 10.4018/978-1-59140-333-3.ch009
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Abstract

Multi-agent systems are highly dynamic since the agents’ abilities and the system configuration often changes over time. In some ways, such multi-agent systems seem to behave like biological processes; new agents appear in the system, some others cease to exist, and communication between agents changes. One of the challenges is to attempt to formally model the dynamic configuration of multi-agent systems. Towards this aim, we present a formal method, namely X-machines, that can be used to formally specify, verify, and test individual agents. In addition, communicating X-machines provide a mechanism for allowing agents to communicate messages to each other. We utilize concepts from biological processes in order to identify and define a set of operations that are able to reconfigure a multi-agent system. In this chapter we present an example in which a biology-inspired system is incrementally built in order to meet our objective.

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Dedication
Table of Contents
Acknowledgments
Marian Gheorghe
Chapter 1
Gheorghe Paun
Membrane computing is a branch of natural computing whose initial goal was to abstract computing models from the structure and the functioning of... Sample PDF
Membrane Computing: Main Ideas, Basic Results, Applications
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Chapter 2
Vincenzo Manca, Giuditta Franco, Giuseppe Scollo
Classical dynamics concepts are analysed in the basic mathematical setting of state transition systems where time and space are both completely... Sample PDF
State Transition Dynamics: Basic Concepts and Molecular Computing Perspectives
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Chapter 3
Lila Kari, Elena Losseva, Petr Sosik
This chapter looks at the question of managing errors that arise in DNA-based computation. Due to the inaccuracy of biochemical reactions, the... Sample PDF
DNA Computing and Errors: A Computer Science Perspective
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Chapter 4
Carlos Martin-Vide, Victor Mitrana
The goal of this chapter is to survey, in a systematic and uniform way, the main results regarding different computational aspects of hybrid... Sample PDF
Networks of Evolutionary Processors: Results and Perspectives
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Chapter 5
Andrés Cordón-Franco, Miguel A. Gutiérrez-Naranjo, Mario J. Pérez-Jiménez, Agustín Riscos-Núñez
This chapter is devoted to the study of numerical NP-complete problems in the framework of cellular systems with membranes, also called P systems... Sample PDF
Cellular Solutions to Some Numerical NP-Complete Problems: A Prolog Implementation
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Chapter 6
Jean-Louis Giavitto, Olivier Michel
Biology has long inspired unconventional models of computation to computer scientists. This chapter focuses on a model inspired by biological... Sample PDF
Modeling Development Processes in MGS
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Chapter 7
Richard Gergory, Richard Vlachos, Ray C. Paton, John W. Palmer, Q. H. Wu, Jon R. Saunders
This chapter describes two approaches to individual-based modelling that are based on bacterial evolution and bacterial ecologies. Some history of... Sample PDF
Computing Bacterial Evolvability Using Individual-Based Models
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Chapter 8
Gabriel Ciobanu
In this chapter a model of the molecular networks, created by using a network of communicating automata, is described as a dynamic structure... Sample PDF
On a Formal Model of the T Cell and Its Biological Feedback
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Chapter 9
Petros Kefalas, G. Eleftherakis, I. Stamatopoulou
Multi-agent systems are highly dynamic since the agents’ abilities and the system configuration often changes over time. In some ways, such... Sample PDF
Formal Modelling of the Dynamic Behaviour of Biology-Inspired, Agent-Based Systems
$37.50
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