Economies work in complex ways that are difficult to model unless major simplifications are introduced. Computer simulations can help represent the complexity of reality and the actions and reactions of economic actors. The models described in this manual are inhabited by agents who interact with one another and their environment, and who modify their behaviour through learning. Model-building is simplified by programme protocols and adopting frameworks that explicate the role of the environment, agents, and behaviour rules. These methodologies can be extended to the exploration of social networks (businesses and business systems) for purposes of both theoretical analysis and practical application (productive context simulation, banking systems, industrial business systems). This is an extremely novel field of study that is only beginning to enter university classrooms, chiefly in study programmes concerning business administration, economics, management, and computer science. The text's value is enhanced by a website offering additional technical details, software supplements, and simulation programmes.

Contents: 1. Introduction: "From Outside Economics" - 2. Agent-Based Models: An Introduction - 3. Using Simulations in Economics - 4. Critique and Growth of the New Methodology - 5. A Reply to Criticism: Methodologies for Defining Simulation Models - 6. Agents: Computers, Cognitive Science, Applications - 7. Building Agents - 8. Cognitive Processes and Studying Emergent Properties in Agent-Based Models - 9. Learning: Neural Networks, Genetic Algorithms, Classification Systems - 10. Building Intelligent Agents with Evidence Theory - 11. Time, Causality, and Event Synchronisation in Models - 12. Structure of Communication among Agents - 13. Instruments: An Introduction - 14. Swarm - 15. JAS - 16. NetLogo - 17. A Stock Exchange Simulation with Swarm - 18. A Neo-Keynesian Simulation with Heterogeneous Agents - 19. Businesses as a Typical Context for Complexity - 20. Simulation Levels for Business - 21. jEs and jEs Open Foundation - 22. Experiments with Human Agents in a Simulation Context - 23. Production Optimisation (Textile Cycle Application) - 24. Business Systems Organisation - 5. Operational Rationalisation through Territorial Action - 26. Agent Simulation and High Capital Intensity Industries - 27. A Summary: From What-If Analysis to Business Evolution.

Pietro Terna teaches Information Technology and Simulation in Economics at the University of Turin.