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

2. 2 MAIA 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. 3 MAIA Applications Domains Wood-fuel market E-Waste recycling Consumer lighting Basic income grants Family-based care … Commonalities Domain characteristics ‘What-if’ analysis of policies Problem-owners /domain experts had limited simulation knowledge

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

5. 5 MAIA What is MAIA? MAIAM odeling A gents based on I nstitutional A nalysis Formal meta-model Institutional perspective (IAD – Ostrom) Web based design tool Declarative rather than procedural Semi-automatic simulation generation

6. 6 MAIA MAIA Architecture The MAIA meta-model finetuning

7. 7 MAIA 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. 8 MAIA Individuals do activities (repetitive) Rules created to manage activities 1- Rules accepted by everyone 2- Used in practice 3- Durability 1- Rules accepted by everyone 2- Used in practice 3- Durability Institutions outcomes affect others too By product of interactions

9. 9 MAIA 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. 10 MAIA Institutional Analysis and Design Elinor Ostrom Nobel laureate 1933-2012 unit of analysis

11. 11 MAIA Institutional Analysis and Development Framework (IAD) Physical world Community Rules Action Arena Patterns of interaction Action Situation Participants Outcomes Evaluation Criteria 1.Position rules 2.Boundary rules 3.Authority rules 4.Aggregation rules 5.Scope rules 6.Information rules 7.Payoff rules 1.Position rules 2.Boundary rules 3.Authority rules 4.Aggregation rules 5.Scope rules 6.Information rules 7.Payoff rules Resources, preferences, information and selection criteria 1.Participants 2.Positions 3.Actions 4.Potential outcomes 5.Functions that map actions into outcomes 6.Information 7.Cost and benefits 1.Participants 2.Positions 3.Actions 4.Potential outcomes 5.Functions that map actions into outcomes 6.Information 7.Cost and benefits

12. 12 MAIA 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. 13 MAIA MAIA Meta model

14. 14 MAIA Collective structure = set of agents

15. 15 MAIA Constitutive Structure

16. 16 MAIA Institutions: ADICO

17. 17 MAIA Physical components

18. 18 MAIA Operational structure

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

20. 20 MAIA 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. 21 MAIA From rules to code

22. 22 MAIA Agent behaviour

23. 23 MAIA MAIA Approach declarative

24. 24 MAIA 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. 25 MAIA 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. 26 MAIA Benefits of MAIA Four completed case studies & 5 other users: Diverse range of concepts: makes you think about the things that you may need to consider in your model. Easy to follow by no-programmers Team of Developers Problem Owner Programmer Or Translator Software System Analyst (Social Scientist) MAIA

27. 27 MAIA MAIA Architecture More info: a.ghorbani@tudelft.nl More info: a.ghorbani@tudelft.nl