1. Multi-Agent Model to Multi-Process Transformation A Housing Market Case Study Gerhard Zimmermann Informatik University of Kaiserslautern

2. 2 Overview 1.Introduction 2.The Case Study 3.The Multi-Agent Model 4.The Transformation Process 5.Experiments 6.Conclusion

3. 3 1. Introduction Research goal: User activities in computer simulations of the built environment Problems to be solved: 1.Observation of user behavior and preferences 2.Dynamic formal model of user activities 3.Integration of user activity model with built environment model 4.Mapping of the model into a simulator 5.Validation of model and simulator 6.Definition of experiments 7.Execution and evaluation of experiments

4. 4 Open Questions Can the simulation of user activities provide us with knowledge that we did not enter into the simulator? Can the simulation of user activities make the design and decision process more efficient? produce better results? produce more reliable results?

5. 5 2. The Case Study household discontent household discontent household content town market property activity center free property city

6. 6 offered property profile offered property profile decision process for each household ideal property utility household profile current property profile offered property profile utility metric household preferences current property utility offered property utility current satisfaction offer satisfaction criteria content discontent take reject

7. 7 diversity and dynamics different household types have different preferences and profiles that change dynamically aging, marriage, birth, job change,... households migrate into or out of town all properties have different profiles that change over time aging, renovation, market value,... new properties are added to, old ones taken from the market construction, land use changes,... ideal application for agents!

8. 8 3. The Multi-Agent Model Agent: Autonomy:autonomous dynamic entity that can Pro-activeness: act based on its own state, parameters, behavior, Reactivity: react to messages from other agents or the environment, Social ability: send messages to other agents or the enviroment Intelligenz:knowlege, learning, belief, emotion,... Multi-Agent System: System of many different communicating agents that exist, act, and react concurrently in an environment

9. 9 more definitions Multi-Agent Model: Model of a specific multi-agent system Modeling Technique: Technique for creating models, based on an informal or formal modeling language Multi-Agent System Computer Simulation: Implementation of a multi-agent model, based on an implementation language

10. 10 simulator production process modeling process system of agents multi-agent simulation implementation process multi-agent model modeling language implementation language reality

11. 11 model refinement model model stucturemodel behavior aggregation hierarchy communication structure agent behavior object types channels messages finite state machines SDL block types SDL channels signals SDL processes code SDT run-time system computer

12. 12 agent behavior extended finite state machine (EFSM) state transition: state1 activity state2 trigger message condition timer waitForOffer calcOfferUtilities; sortOffers; waitForConfirm acceptOffer -> market market -> newOffers example waitForOffer waitForConfirm acceptOffer -> market market -> newOffers abstraction

13. 13 agent process state transition graph s1 s2 s6 s3 s5 s4 channel (m1, m2) channel (m3, m4, m5) channel (m6, m7)

14. 14 multi-agent model a1a1 s1 s2 s6 s3 s5 s4 channel (m1, m2) a1a1 s1 s2 s6 s3 s5 s4 channel (m5, m6) a1a1 s1 s2 s6 s3 s5 s4 channel (m5, m2)

15. 15 MTC – message transition charts offer handshake scenario newData waitForOffer waitForConfirm household content [currSatisfaction<0] idle content waitForOffer getOffer newOffers acceptOffer confirm [property=free][property<>free] market

16. 16 4. The Transformation Process problem description HTML table environment HTML table scenarios message/transition charts object type structure HTML table tasks/strategies HTML table process structure SDL graph finite state machines SDL graph message structure SDL list PROTAGOnIST- Generator simulator C code Telelogic- Generator 0.8h 7.5h 0.3h 61h 1.5h 2.5h 7.8h total=89h

17. 17 example transformation Problem Description: Need: accept and react to offers Task: -> Household evaluate offers and accept best offer waitForOffer waitForConfirm acceptOffer newOffers Strategy: MTC: waitForOffer calcOfferUtilities; sortOffers; waitForConfirm acceptOffer newOffers refined MTC: waitForOffer: ^newOffer(offers)/ !calcOfferUtilities; !sortOffers; ^acceptOffer(best); HTML: waitForOffer newOffers(offers) calcOfferUtilities sortOffers acceptOffer(best) waitForConfirm SDL process:

18. 18 5. Experiments Problem: missing statistical data on household preferences and profiles property profiles assignment of household types to property types Makeup of data: 16 household types (individual number and income) type distribution according to German census data corresponding property types random distribution of locations rent and value in relation to “Sozialwohnungen” Starting assignment: initialization run with all households migrating into town

19. 19 initialization Initial conditions: 500 households, 550 properties initial random urgencies stable conditions: after 65 days 471 households found a property 3600 offers with 1..3 properties each / 7 offers per household 1700 empty offers 1800 acceptOffer messages 1350 rejected acceptOffer

20. 20 initialization

21. 21 50 new properties at day 150

22. 22 6. Conclusion Multi-agent models provide a good mapping of diverse active individuals (humans or objects) Autonomous processes provide a good implementation of multi-agent models Modeling and implementation can be efficiently supported by software engineering processes Modeling and implementation can be efficiently supported by computer tools The housing market case study demonstrates this efficiency and shows “human” behavior