Concepts for Complexity Modelling -- Models and Simulations in the Historical Emergence of the Science of Complexity -- About the Predictability and Complexity of Complex Systems -- What Makes a System Complex? - An Approach to Self Organization and Emergence -- A formalism for multi-level emergent behaviours in designed component-based systems and agent-based simulations -- Emergence of Chaos and Complexity During System Growth -- Geographical Complex Systems Modelling -- Theory of Reaction-Diffusion and Emergence of the Geographical Forms -- Spatial risks and complex systems : methodological perspectives -- A new classification of catastrophes based on “Complexity Criteria” -- Community Swarm Optimization -- Dynamical Artificial or Natural Complex Networks -- Emergence of Growth and Structural Tendencies During Adaptive Evolution of System -- Complex emergent properties in synchronized neuronal oscillations -- Validation Of A Distributed ‘SmartSpace’ Architecture Through Simulation -- Transport and Traffic Flow -- A Decentralised Approach for the Transportation On Demand Problem -- Modelling Complex Intermodal Freight Flows -- Decision Support Systems -- Modelling the Complexity of Inventory Management Systems for Intermittent Demand using a Simulation-optimisation Approach -- Cooperative Medical Diagnosis Elaboration by Physicians and Artificial Agents -- AgentTime: A Distributed Multi-agent Software System for University’s Timetabling -- Emotion: appraisal-coping model for the “Cascades” problem.

Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deductable from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developped along the chapters, are enable to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.