behavioural rules in multi agent systems max

The behavioural rules in Multi Agent Systems: a “not a toy” approach

The behavioural rules in Multi Agent Systems: a “not a toy” approach

Alessandra LAPUCCI Massimiliano PETRI

Diana POLETTI

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

University of Pisa, Department of Civil Engineering

[m.petri, alessandra.lapucci, diana.poletti]@ing.unipi.it

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

The starting point A first award

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Topics

1. Knowledge Need

2. A particular MAS: Activity-Based Model

3. “Citylive” Structure and Case Study Application

A.The EnvironmentB.The AgentsC.The Rules : knowledge extraction

from data

4. The model implementation

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Interventions on:Interventions on:• Road Conditions Road Conditions • Traffic RegulationsTraffic Regulations• Public TransportPublic Transport• Road worksRoad works• Activities Activities (re)localization(re)localization• Activities Activities opening/closingopening/closing times times • Limited Access AreasLimited Access Areas……………………..

““City Live” City Live” modelmodel

SimulationsSimulations

Effects on:Effects on:• Traffic and CongestionTraffic and Congestion• Public Transport DemandPublic Transport Demand• Parkings DemandParkings Demand• Travel Time to WorkTravel Time to Work• Travel Time to SchoolTravel Time to School• Travel Time to Various Travel Time to Various • Services ….Services ….

“ “ City as Living City as Living Organism”Organism”

Function AssessmentFunction Assessment==

Life QualityLife Quality

“City-Live” model answersKnowledge Need

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Pop

ula

tion

Su

rvey

Pop

ula

tion

Su

rvey

- A) - A) an an EnvironmentEnvironment

- B) - B) a set of Agents,a set of Agents, active entities of the active entities of the systemsystem

- - C)C) a set of “Rules”a set of “Rules” regulatingregulating agents’s activitiesagents’s activities

The Case Study The Activity-Based Model

SCHEDULINGSCHEDULING- WHERE do city users go? - WHERE do city users go? ((in which servicesin which services) activities ) activities localizationlocalization- HOW do they get there? - HOW do they get there? (by which transport means) traffic (by which transport means) traffic and and - WHERE do they park? - WHERE do they park? public public transporttransport

- WHICH family members are involved?- WHICH family members are involved? family family organizationorganization

- IN WHICH - IN WHICH hours do they move?hours do they move? space space use anduse and- HOW MUCH - HOW MUCH time do they spend?time do they spend? time time consumeconsume- HOW LONG - HOW LONG do they stay?do they stay?- ………… …………

Why sequential Activity-Based model ?

The Case Study

Morning act. diary pattern

Afternooon act. diary

patternEvening

act. diary pattern

The Activity-Based Model

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Region: Tuscany (Italy)

City: Pisa

Region: Tuscany (Italy)

City: Pisa

Residents: approximately 82.000

Surface: 7600 hectares

Residents: approximately 82.000

Surface: 7600 hectares

A) The Environment in“City-Live” The Study Area

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

A Reactive Agent

1. Temporal Geometric Network

2. Geodatabase of activities located in the study area

3. Population data related to the 918 census sections involved

The Environment is structured as e real agent

Behaviours/Attributes vary

through time

through space

according to interactions with agents

The environment is implemented on a G.I.S. platform

It allows efficient and dynamic spatial queries

The environment is implemented on a G.I.S. platform

It allows efficient and dynamic spatial queries

A) The Environment in“City-Live”

City-Live Population Survey Two different City Users

ResidentsCommuter

s

ResidentsCommuter

s

Pisa citycentre

Pisa citycenter Arrival points

Residents Activities

Commuters Activities

CommutersUniverse: the commuters working in the activity with more than 20 employees (source: firm direct contact)Sample: based on a spatial accessibility and homogeneity criteriaResidents

Universe: the total residents in the Census Areas selected (source: Statistical National Agency)Sample: a two-steps sample method

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

City-Live Population Survey Accessibility index

Road Network (with one-way)Census Area centroids

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

City-Live Population Survey Accessibility index

Gravitational Potential

PGa = kj Σj Mj / dajα

where

PGa = Gravitational Potential fotr the Census Area aKj = Census Area j weightMj = Number of emplyees in the Census Area jdaj = Distance between a and j calculated on the Networkalfa = distance sensitiveness

We use this index to create Census Area Clusters based on homogeneous accessibility criteria

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

City-Live Population Survey Accessibility index

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Questionnaire Structure 1 – Personal Data:

Class (commuter, domiciled or resident); Residence/Arrival area in Pisa; Sex; Age Band; Civil Status; Number of Transfers; Single Component Occupation; Individual Salary Range; Educational Qualification; Number of Family Components; Family Composition; Head of a family Age; Number of Children in the Family; Driving Licence Number in the Family; Car Numerousness in the Family.

Indi

vidu

al D

ata

Fam

ily

Dat

a

Questionnaire Structure 2 – Daily Activities:

Activity Type (14); Start/End Activity Period; Activity Localization; Activity Duration; Transportation Means; Reason for Choosing or not Public Transports (specifically requested from Pisa Province) Trip Time; Planning Moment; Accompainment Possibility (number of people).

Questionnaire Structure 3 – Individual preferences :

Preferred transport meansUsed transport meansJudgements about urban services …

Questionnaire StructureCity-Live Population Survey

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Questionnaire StructureCity-Live Population Survey

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

City-Live Population Survey The web site

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

City-Live Population Survey

Personal data survey

The web site

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

City-Live Population Survey

Activity diary data web-GIS

For clients with editing not allowed

(administrations, firms, etc..)For clients with

allowed editing(sample)

The web site

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

City-Live Population Survey Questionnaire: results

LegendResidenceArrival com.Activity

Travel by car

Travel by bikeTravel by busTravel on foot

Activity duration

Ore 12.30-14.00 Tim

e ax

is

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Survey Use - 1

Sample Survey Sample Survey

: :

QuestionnairesQuestionnaires

Sample Survey Sample Survey

: :

QuestionnairesQuestionnaires

Agents:

• Residents inserted in their own Familiar Context

• Singles Commuters

Iterative Proportional Fitting

Whole Population Whole Population

ReconstructionReconstructionWhole Population Whole Population

ReconstructionReconstruction

City-Live B) The Agents

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Examples:

Which choice is made first in the model? Which transport means do an individual choose?At what time does the activity start?….

Knowledge Discovery in Databases

Knowledge Extraction for Model BuildingKnowledge Extraction for Model BuildingKnowledge Extraction for Model BuildingKnowledge Extraction for Model Building

City-Live C) The Rules

Sample Survey Sample Survey

: :

QuestionnairesQuestionnaires

Sample Survey Sample Survey

: :

QuestionnairesQuestionnaires

Survey Use - 2

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

City-Live: C) The Rules Example: Survey & KDD

Decision Tree IF .. THEN .. Rules

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

Cube environmentCity-Live: Activity-Based Model

- It incorporates most of the Activity-based demand techniques.- It allows the input of GIS data and their editing in a ArcGIS-like environment- It distributes model run processes across multiple computer processors, cutting model run times- It contain a scripting language to insert the KDD rules in the choice processes modules- It allows choice aggregation combining the effects of individual choice for such things as travel destination, time of day, cost and parking to provide aggregate representations

L.I.S.T.A. – Laboratorio di Ingegneria dei Sistemi Territoriali e Ambientali

THE END

Alessandra Lapuccialessandra.lapucci@ing.unipi.it

Massimiliano Petrim.petri@ing.unipi.it

Diana Polettidiana.poletti@ing.unipi.it

University of PisaDepartment of Civil Engineering

Thank you !!