Multi-Agent Model to Multi-Process Transformation

A Housing Market Case Study

Gerhard Zimmermann

Informatik

University of Kaiserslautern

2

Overview

1. Introduction

2. The Case Study

3. The Multi-Agent Model

4. The Transformation Process

5. Experiments

6. Conclusion

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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

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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?

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2. The Case Study

householddiscontent

householddiscontent

householdcontent

town

marketproperty

activitycenter

freeproperty

city

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offered property profile

offered property profile

decision process for each household

ideal propertyutility

household profile

current property profile

offered property profile

utility metric

household preferences

current propertyutility

offered propertyutility

currentsatisfaction

offersatisfaction

criteria

content

discontent

take

reject

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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!

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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

enviromentIntelligenz: knowlege, learning, belief, emotion, ...

Multi-Agent System:System of many different communicating agents that exist, act, and react concurrentlyin an environment

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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

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simulator production process

modeling process

system of agents

multi-agent simulation

implementation process

multi-agent model

modeling language

implementation language

reality

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model refinement

model

model stucture model behavior

aggregationhierarchy

communicationstructure

agent behavior

object typeschannelsmessages

finite statemachines

SDL block typesSDL channels

signalsSDL processes

code SDT run-time systemcomputer

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agent behavior

extended finite state machine (EFSM)• state transition:

state1

activity

state2

trigger

message

messageconditiontimer

waitForOffer

calcOfferUtilities;sortOffers;

waitForConfirm

acceptOffer-> market

market ->newOffers

example

waitForOffer

waitForConfirm

acceptOffer-> market

market ->newOffers

abstraction

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agentprocess

state transition graph

s1

s2

s6

s3

s5

s4

channel(m1, m2)

channel(m3, m4, m5)

channel(m6, m7)

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multi-agent model

a1s1

s2

s6

s3

s5

s4

channel(m1, m2)

a1s1

s2

s6

s3

s5

s4

channel(m5, m6)

a1s1

s2

s6

s3

s5

s4

channel(m5, m2)

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MTC – message transition chartsoffer handshake scenario

newData

waitForOffer

waitForConfirm

household

content

[currSatisfaction<0]

idle

idle

idle

contentcontent waitForOffer

getOffer

newOffers

acceptOffer

confirm

[property=free] [property<>free]

market

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4. The Transformation Process

problem descriptionHTML table

environmentHTML table

scenariosmessage/transition charts

object type structureHTML table

tasks/strategies HTML table

process structureSDL graph

finite state machinesSDL graph

message structureSDL list

PROTAGOnIST-Generator

simulatorC code

Telelogic-Generator

0.8h7.5h

0.3h

61h

1.5h

2.5h

7.8h

7.8h

total=89h

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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:

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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

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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

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initialization

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

10 20 30 40 50 60 70 80

days

avg

Sat

isfa

ctio

n

0

100000

200000

300000

400000

500000

tota

lRen

t

avgSatisfaction totalRent

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50 new properties at day 150

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

100 150 200 250 300 350 400

days

avg

Sat

isfa

ctio

n

0

100000

200000

300000

400000

500000

tota

lRen

t

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6. Conclusion

• Multi-agent models provide a good mapping of diverse active individuals (humans or objects)

• Autonomous processes provide a goodimplementation 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