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Agent-based Modeling and Simulation for the Social Scientist

Agent-based Modeling and Simulation for the Social Scientist. MAIA. Amineh Ghorbani, Virginia Dignum, Pieter Bots, Gerard Dijkema, Bert Belder. Goal. Framework for agent-based conceptualization and simulation Rich enough to capture a diverse range of social systems

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Agent-based Modeling and Simulation for the Social Scientist

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  1. Agent-based Modeling and Simulation for the Social Scientist MAIA Amineh Ghorbani, Virginia Dignum, Pieter Bots, Gerard Dijkema, Bert Belder

  2. Goal • Framework for agent-based conceptualization and simulation • Rich enough to capture a diverse range of social systems • Support developers with little/no programming/software engineering knowledge • Application areas • Policy design / public goods problems • Social systems: complex behavior / discrete entities • Approach • Collaborative modelling • Institutional analysis (Ostrom) • Model driven engineering (MDE) • meta-modeling and semi-automatic code generation

  3. Applications Domains Commonalities Domain characteristics ‘What-if’ analysis of policies Problem-owners /domain experts had limited simulation knowledge • Wood-fuel market • E-Waste recycling • Consumer lighting • Basic income grants • Family-based care • …

  4. Common characteristics • Effect of incentives / policies • Social networks and institutions • Individual interests • Global consequences • Multi-criteria decision making

  5. What is MAIA? • ModelingAgentsbasedonInstitutionalAnalysis • Formal meta-model • Institutional perspective (IAD – Ostrom) • Web based design tool • Declarative rather than procedural • Semi-automatic simulation generation

  6. MAIA Architecture • The MAIA meta-model finetuning

  7. Institutions An institution is any structure or mechanism of social order and cooperation governing the behavior of a set of individuals within a given human community. Institutions are identified with a social purpose and permanence, transcending individual human lives and intention by enforcing rules that govern cooperative human behavior

  8. Institutions 1- Rules accepted by everyone 2- Used in practice 3- Durability By product of interactions Rules created to manage activities Individuals do activities (repetitive) outcomes affect others too

  9. Institutional frameworks • Institutions have two sides: • Enable interactions, provide stability, certainty, and form the basis for trust. • Cause power relations and may hamper reform. • Important to understand effects of institutions • Institutional (re)design Analyze and Understand for Design Institutional Frameworks

  10. Institutional Analysis and Design unit of analysis Elinor Ostrom Nobel laureate 1933-2012

  11. Institutional Analysis and Development Framework (IAD) Participants Positions Actions Potential outcomes Functions that map actions into outcomes Information Cost and benefits Position rules Boundary rules Authority rules Aggregation rules Scope rules Information rules Payoff rules Action Arena Physical world Action Situation Patterns of interaction Community Evaluation Criteria Participants Rules Outcomes Resources, preferences, information and selection criteria

  12. Extending IAD • Formalization of concepts • MAIA formal model • Robust information and consensus • MAIA online tool supports flexible conceptualization through participatory exploration • Supports reflection and discussion • Outward looking • Information collected directly reflects the experiences and perceptions of stakeholders themselves

  13. MAIA Meta model

  14. Collective structure = set of agents

  15. Constitutive Structure

  16. Institutions: ADICO

  17. Physical components

  18. Operational structure

  19. MAIA Modelling Environment http://test1.eeni.tbm.tudelft.nl/maia/

  20. Translation to Java Code • MAIA MM is developed as an e-core model • EMF environment in Eclipse for model-driven software development. • XML specification. • Output of MAIA web-tool is based on MAIA MM • Explicit, fixed, rules to convert MAIA model (XML) to Java simulation • Current work: translator code, for automatic generation of code from a MAIA-based model.

  21. From rules to code

  22. Agent behaviour

  23. MAIA Approach declarative

  24. Conclusions MAIA framework for agent-based simulation • Rich enough to capture a diverse range of social systems • Support developers with little/no programming/software engineering knowledge • Based on Institutional analysis (Ostrom) • Formal model • Verification • Model driven engineering (MDE) for semi-automatic code generation

  25. Future work • Extend and validate code generation • Visualisation of simulation results • Library of agent behaviours • Extensive evaluation • Transformation of MAIA models into other simulation environments (e.g. Netlogo or Repast)

  26. MAIA Architecture More info: a.ghorbani@tudelft.nl

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