1. Agent-based Simulation
Hardy Hanappi

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

3. Past The technological trajectory Impact 1: agents in biology
… 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 Different scope choice
… 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 A recipe for ABM Choose a topic Identify the major agents
Construct the internal models
Empirical data (historical)
Econometric estimation
Software implementation
Systematic result generation

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

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

9. Semantics Domain specific features Agent specific properties
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: