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Agent-based Simulation

Agent-based Simulation. Hardy Hanappi www.econ.tuwien.ac.at Hanappi@tuwien.ac.at. Content. Past History of ABM Present The essence of ABM Future Areas of future evolution of ABM. Past. The technological trajectory … and its methodological consequences Impact 1: agents in biology

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Agent-based Simulation

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  1. Agent-based Simulation Hardy Hanappi www.econ.tuwien.ac.atHanappi@tuwien.ac.at

  2. Content • Past • History of ABM • Present • The essence of ABM • Future • Areas of future evolution of ABM

  3. Past • The technological trajectory • … and its methodological consequences • Impact 1: agents in biology • Species, classes, entrepreneurs, families, entrepreneurs • Impact 2: evolution of networks • Quantum theory, microbiology, heterogeneous nodes

  4. Present 1 • Programs instead of equation systems • … simulation runs instead of investigation of properties • Models of models used by agents • Perception, embedding in internal model, choice of action (timing!) • Strong specification – Adequacy • Heterogeneous agents in a specific environment

  5. Present 2 • Shift of methodology • … no homo e., no repr. firm, no equ. consideration, etc ... • Different scope choice • Oriented on object of investigation, not technical feasability • Emergence of knowledge • Atomism (meth. Ind.) versus emergence at all levels

  6. Present 3 • Choose a topic • Identify the major agents • Construct the internal models • Empirical data (historical) • Econometric estimation • Software implementation • Systematic result generation A recipe for ABM

  7. The Future of Agent-based Modelling Three dimensions Syntax Pragmatics Semantics

  8. Syntax • Language evolution – standards • Reproducibility issues • Language evolution – operators • … copy, pointers, … • Language evolution – switches • Data-program-data- … • Time handling

  9. Semantics • Domain specific features • E.g. Micro-Meso-Macro, information goods, … • Agent specific properties … perception, instruments, typical short-cuts, goals, communication … • Environments • E.g. market, bargaining space

  10. Pragmatics • Embedding as ‘brain extensions’ • E.g. tool for applied game theory • Teaching of incentive compatibility • Enlightenment goals • Study of social development • Emergence of global classes and their dynamics

  11. Thank you for your attention Hardy Hanappi Publications for download: http://www.econ.tuwien.ac.at/hanappi/publications.html Hanappi@tuwien.ac.at

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