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Applications range from modelling agent behaviour in the stock market ( Arthur et al, 1997) and supply chains ( Macal, 2004a) to predicting the spread of epidemics ( Bagni et al, 2002) and the threat of bio-warfare ( Carley et al, 2006), from modelling the adaptive immune system ( Folcik et al, 2007) to understanding consumer purchasing behaviour ( North et al, 2009), from understanding the fall of ancient civilizations ( Kohler et al, 2005) to modelling the engagement of forces on the battlefield ( Moffat et al, 2006) or at sea ( Hill et al, 2006), and many others. Agent-based modelling offers a way to model social systems that are composed of agents who interact with and influence each other, learn from their experiences, and adapt their behaviours so they are better suited to their environment.Īpplications of agent-based modelling span a broad range of areas and disciplines. The emphasis on modelling the heterogeneity of agents across a population and the emergence of self-organization are two of the distinguishing features of agent-based simulation as compared to other simulation techniques such as discrete-event simulation and system dynamics. Patterns, structures, and behaviours emerge that were not explicitly programmed into the models, but arise through the agent interactions. By modelling systems from the ‘ground up’-agent-by-agent and interaction-by-interaction-self-organization can often be observed in such models. By modelling agents individually, the full effects of the diversity that exists among agents in their attributes and behaviours can be observed as it gives rise to the behaviour of the system as a whole. Agents have behaviours, often described by simple rules, and interactions with other agents, which in turn influence their behaviours. He has been working at The AnyLogic Company for more than twenty years and has a deep and extensive knowledge of simulation and AnyLogic.Agent-based modelling and simulation (ABMS) is a relatively new approach to modelling complex systems composed of interacting, autonomous ‘agents’. Ilya Grigoryev has been a simulation consultant to several organizations.
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He has given numerous public training sessions in the U.S., Europe, Africa, and Asia. He is the author of AnyLogic documentation and AnyLogic training courses. Ilya Grigoryev is Head of Training Services at The AnyLogic Company.
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You can consider this textbook as your first guide for studying AnyLogic and simulation. This book also gives some simulation theory and illustrates different modeling methods.
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This modeling and simulation book can be downloaded as a pdf. The freely supplied software gives readers the ability to follow the steps provided in the tutorials and learn simulation by practice. It contains simulation theory and educational examples for all three model-building methods: agent-based modeling, discrete event modeling and system dynamics. The book is ideal for studying computer simulation and modeling with the free AnyLogic Personal Learning Edition. This simulation book is designed for use in self-education and in university. This is a practical textbook on AnyLogic simulation software from its developers.