PhD dissertation 2010

Designing andProgrammingOrganizationalInfrastructures

for Agentssituated in

Artifact-basedEnvironments

Piunti, M.

Introduction

Objectives

A unifyingapproach toMASProgramming

EmbodiedOrganizations

Implementation

Conclusions

Designing and ProgrammingOrganizational Infrastructures for Agentssituated in Artifact-based Environments

European PhD

Michele [email protected]

ALMA MATER STUDIORUMUniversità di Bologna – DEIS

Bologna

April 30th, 2010

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[email protected]




Piunti, M.

Introduction

Objectives



Implementation

Conclusions

European PhD

Tutor

• prof. Antonio Natali

Co-Tutor

• prof. Alessandro Ricci

• prof. Andrea Omicini

Reviewers

• Mehdi Dastani (Utrecht University - Utrecht, Netherlands)

• Juan Antonio Rodriguez Aguilar (AI Research Institute - Barcelona,Spain)

Collaborations

• Istituto Scienze e Tecnologie della Cognizione - I.S.T.C. - C.N.R.,Roma.

• G2I Group - Ecole Nationale Supérieure des Mines, St-Etienne -France.

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Outline

1 Introduction

2 Objectives

3 A unifying approach to MAS Programming

4 Embodied Organizations

5 Implementation

6 Conclusions

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

IntroductionChallenges of current IT systems:

Open Systems

• Heterogeneous entities interacting at runtime;

• Entering and leaving the system directed by differentinterests/objectives.

Complex Systems

• Complex structure, multiple functionalities;

• Global dynamics derive from local ones.

Taking an Organizational Perspective

• Human organizations as a suitable model to build computationalsystems

• Multi-Agent Organizations [Ferber et al., 2003, Gasser, 2001,Boissier et al., 2006, Dignum, 2009, Coutinho et al., 2009].

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Multi Agent Systems (MAS)

Agent

“An agent is a computer system that is situated in some environmentand that is capable of autonomous action in this environment in orderto meet its design objective.” [Wooldridge and Jennings, 1995]

Organizations

“...can be understood as complex entities where a multitude of agentsinteract, within a structured environment aiming at some globalpurpose.” [Dignum, 2009]

EnvironmentsFirst class abstraction containing those resources not modellable asagents [Weyns et al., 2007]

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Multi Agent Systems (MAS)Agent

“An agent is a computer system that is situated in some environmentand that is capable of autonomous action in this environment in orderto meet its design objective.” [Wooldridge and Jennings, 1995]

Organizations

“...can be understood as complex entities where a multitude of agentsinteract, within a structured environment aiming at some globalpurpose.” [Dignum, 2009]

EnvironmentsFirst class abstraction containing those resources not modellable asagents [Weyns et al., 2007]

GOALSBELIEFS

PLANSACTIONS

AGENTS

ROLES

SANCTIONS/REWARDS

MISSIONS

NORMS

ORGANIZATIONS

DEONTIC RELATIONS?INTERNALEVENTS

SERVICES

RESOURCES

COMPONENTS

ENVIRONMENTS

LEGACY

PERCEPTIONS

DUTIES

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

MAS ProgrammingAgent Programming

Jason [Bordini et al., 2007], Jadex [Pokahr et al., 2005], 2APL [Dastani, 2008], etc.

Organization Programming: platforms and approaches

AGR/MADKIT [Ferber et al., 2003], PowerJade [Baldoni et al., 2008], Electronic

Institutions [Esteva et al., 2004], S-MOISE + [Hübner et al., 2005], OPERA

[Dignum, 2003], etc.

Environment Programming

MASQ, AGRE [Stratulat et al., 2009, Báez-Barranco et al., 2006], Normative

Objects [Okuyama et al., 2009], Situated Electronic Institutions

[Campos et al., 2008], etc.

A seamless integration of entities and mechanisms is stillneeded

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

1 Introduction

2 Objectives



5 Implementation

6 Conclusions

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Outline

1 Introduction

2 Objectives



5 Implementation

6 Conclusions

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Objectives

To embody organizations within the agents’environment

• To provide unifying approach to MAS programming

Several outcomes at an application level:• To reconcile agents and their work environments with institutional

dimensions (i.e. organizations);• To exploit a strong notion of agency, i.e., mental attitudes

(purposes, knowledge), events, perception

• Interoperability and Openess

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Objectives

To embody organizations within the agents’environment

• To provide unifying approach to MAS programming

Several outcomes at an application level:• To reconcile agents and their work environments with institutional

dimensions (i.e. organizations);• To exploit a strong notion of agency, i.e., mental attitudes

(purposes, knowledge), events, perception

• Interoperability and Openess

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Chosen ApproachIn human organizations infrastruc-tures are explicitely conceived foreasing complex activities/tasks.

Cross disciplinary approach:• Intelligent use of Space

[Kirsh, 1995]• Theory of Social Actions

[Castelfranchi, 1998]

Environments are instrumented with

specific Infrastructures

Aiding purposes, easing agent works

EnvironmentArtifacts

Staff Agents

Staff Agent

Patient Agents

VisitorAgents

Infrastructures

To provide a set of coherent Infrastructures instrumenting environments

for implementing Organizations and Environments

[Piunti et al., 2009a, Piunti et al., 2009b]

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Outline

1 Introduction

2 Objectives



5 Implementation

6 Conclusions

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Unifying approach to MASProgramming

AGENT(S)A-E

O-EA-O

ENVIRONMENT

ORGANIZATION

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Unifying approach to MASProgramming

AGENT(S)A-E

O-EA-O

ENVIRONMENT

ORGANIZATION

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Environment Programming

A&A meta-model for MAS [Omicini et al., 2008] :

Agents Autonomous andself-interested entitiesencapsulating theircontrol.

Artifacts Non-autonomousentities.

Workspaces Virtual containers ofagents and artifacts,defining the topologyand the properties ofthe environment.

Hospital workspace

Agents

Artifacts

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Artifact Metamodel

Artifact Usage Interface

Usage Interface Control

nameparams

Operation

triggercontrol

Observable Event

generate

11

Observable Property

namevalue

update

Manualfunctionsoperating instructions

1

OpControlName(Params)

OpControlName(Params)

...

Value

ARTIFACT

MANUAL

OBSERVABLE

EVENTS

GENERATION

<EvName,Params>

OPERATION X

LINK

INTERFACE

OPERATION Y

OBSERVABLE

PROPERTIES

USAGE

INTERFACE

ObsPropName

ValueObsPropName

......

Usage Interface and Observable Properties

• Basic building block for decentralized MAS environments

• “Object” at an agent level of abstraction

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Model for A-E Interactions

AGENT(S)A-E

ENVIRONMENT

O-EA-O

ORGANIZATION

Actions and Perceptions

• Native capabilities of agents;

• Addressed at artifacts (and workspaces) functionalities

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Agent-Artifact InteractionMetamodel

Artifact Usage Interface

Usage Interface Control

nameparams

Operation

triggercontrol

Observable Event

generate

Agent11 use

perceive

Observable Property

namevalue

perceiveobserve

update

Manualfunctionsoperating instructions

1 consult

Workspacejoinquit

Work Environment

Pragmatic and Epistemic Actions

• Agent-Environment (A-E) interactions are based on the notion of:Usage and Perception [Piunti and Ricci, 2008]

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

CArtAgO Infrastructure

focus

makeArtifact

use

BillingMachine

Hospital Workspace

CArtAgO nodeAgent Platform(s)

Bridge(i.e. c4Jason,

c4Jadex)+

payments

pay

Orthogonality

• Heterogeneous agents (Jason,Jadex) work in artifact basedenvironments;

• Integration technologies (bridges)[Piunti et al., 2008, Ricci et al., 2009].

Improved repertoire of agent’s actions:

• .joinWorkspace

• .makeArtifact

• .lookupArtifacts

• . ...

• .use

• .observeProperty

• .focus

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Environment ManagementInfrastructures

Hospital Scenario

Artifacts are viewed as a set of re-sources exploitable by agents• Goal Oriented Interaction• Externalisation• Coordination

For instance in Jason:+!execute_pay: artifact_id(billing, BmId)& payment(Params)<- cartago.use(BmId, pay(Params),

Receipt).

Terminal

sendBillsendFee

SurgeryTablet

signDocsignPat

visits

BillingMachine

pay

payments

AgentPlatforms

EMIENVIRONMENTARTIFACTS

HospitalWorkspace

STAFF

STAFF

VISITOR

VISITOR Desk

bookVisit

reservations

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Organization Programming

AGENT(S)

A-O

A-E

O-E

ENVIRONMENT

ORGANIZATION

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

MOISE Model

Organization is specified by defining a set of dimensions[Hübner et al., 2007]1:

Structural Roles, Groups, RelationshipsFunctional Goals, Missions, deadlines (time-to-fulfill)

Deontic Norms, Obligations

1For the adoption of MOISE we would thank the G2I group at Ecole des Mines, St-Etienne.23 / 56




Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Hospital Scenario: Structuraldimension

StaffGroup

Doctor

Staff

1..1

0..1

VisitGroup

Escort Patient

0..1 1..1

inheritancecomposition

ROLEGROUP

acquaintance

communication

authority

compatibility

LINKS INTRA-GROUP EXTRA-GROUPLEGEND

min..max

Surgery RoomGroup

1..10..NVMAX

Visitor

ABS ROLE

(a) Structural Specification in Moise in the Hospital Scenario

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Piunti, M.

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Objectives



Implementation

Conclusions

Hospital Scenario: Functionaldimension

enterthe room

book the visit

visit

visitor scheme

observe

send fee

monitorscheme

mSanpayvisit

enforcement

sendbill

mRew

[1 day] [1 day][30 minutes]

do thevisit

mVisit mVisit

mPaymPatient

exitmVisit

[5 minutes]

LEGEND

goalmissions

[TTF] sequence choice parallelism

visitorSch monitorSch

mStaff

Doctorscheme

mDoc docSch

visit patient

mDoc

[30 minutes]

[30 minutes]

(b) Functional Specification in Moise

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Hospital Scenario: Deonticdimension

(c) Deontic Specification in Moise

Controlling agent’s autonomy with Norms

• Organization prescribes a set of norms (obligations, prohibitionspermissions);

• Agents may decide to violate norms;

• Once a norm is violated the organization configuration has to beupdated

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Organization ManagementInfrastructures

• ORA4MAS [Hübner et al., 2009] OMI is composed by a set ofartifacts providing agents with organizational functions;

• Artifact initialized with the MOISE specification

• Define also A-O

Norm violations are relevant

events stored as artifact events

For instance in Jason:+!commit_mission(M): artifact_id(sch, SchId)<- cartago.use(SchId,

commitMission(M)).

HospitalWorkspace

AgentPlatforms

OMI ORGANISATIONALARTIFACTS

ESCORT

VISITOR

VISITOR

SchemeBoards

GroupBoards

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Outline

1 Introduction

2 Objectives



5 Implementation

6 Conclusions

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Embodied Organizations

AGENT(S)A-E

O-EA-O

ENVIRONMENT

ORGANIZATION

HospitalWorkspace

AgentPlatforms

EMIENVIRONMENT

ARTIFACTS


DeskBillingMachine

SurgeryTablet

Terminal

STAFF

STAFF

VISITOR

VISITOR

SchemeBoards

GroupBoards

E-O Integration• To transer events and changes

occurring inside environment tothe organization

• and the other way

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Embodied Organizations

AGENT(S)A-E

O-EA-O

ENVIRONMENT

ORGANIZATION

HospitalWorkspace

AgentPlatforms

EMIENVIRONMENT

ARTIFACTS


DeskBillingMachine

SurgeryTablet

Terminal

STAFF

STAFF

VISITOR

VISITOR

SchemeBoards

GroupBoards

E-O Integration• To transer events and changes

occurring inside environment tothe organization

• and the other way

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Constitutive RulesConstitutive Rules [Searle, 1964]

• Typical of human societies (Social Reality [Searle, 1997] )

• The reification of a state in a particular context may constitute therealization of a particular institutional/organizational fact

EnvironmentManagement Infrastructure

OrganisationManagementInfrastructure

count-as

enact

count-as

Agents

• Used to automate particular dynamics between E-O:

• “Entering an ambulatory room count-as adopting the rolepatient”

• “Finalizing the payment operation on the billing machinecount-as achieving the goal pay”

• “A sold out in the visit schedule enact the suspension of thebooking service”

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Constitutive RulesConstitutive Rules [Searle, 1964]

• Typical of human societies (Social Reality [Searle, 1997] )

• The reification of a state in a particular context may constitute therealization of a particular institutional/organizational fact

EnvironmentManagement Infrastructure

OrganisationManagementInfrastructure

count-as

enact

count-as

Agents

• Used to automate particular dynamics between E-O:

• “Entering an ambulatory room count-as adopting the rolepatient”

• “Finalizing the payment operation on the billing machinecount-as achieving the goal pay”

• “A sold out in the visit schedule enact the suspension of thebooking service”

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Embodied OrganizationMetamodel

O-E functional relationships defined by Constitutive Rulesbased on Events:

Constitutive Rule

(Emb-Org-Rule)

Count-asRule

EnactRule

Embodied Organization

EnvironmentEvent

Organization Event

EventEv TypeEv Value

Produces

Triggers

1..n

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Outline

1 Introduction

2 Objectives



5 Implementation

6 Conclusions

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Formal ModelImplementing Emb-Org-Rules implies to re-engineerCArtAgO by indruducing:Workspace EventsWorkspace rules

MAS = 〈Ws〉Ws = {〈wsn,〈Ag,Ar ,Art ,Ev ,M,R, t〉〉}Ag = {〈agid ,ags,agEv ,agpr 〉}Ar = {〈arid ,art , I,O,P,V 〉}

Table: Structures inside a MAS (implemented by CArtAgO)

Formal model described by a transition system in the thesis

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Workspace Events

Ws = 〈Ag,Ar ,Art ,Ev,M,R, t〉

WORKSPACEEVENTS ( Ev ) R Art M

Workspace Kernel

CArtAgOWorkspace Events

Are records of significant changes in theapplication domain (i.e., state/processes).

1 Can be perceived by agents focusingartifacts

2 Can be collected and ranked at theworkspace level

ev = 〈evt ,evv 〉Event pairs (type, value) from Observable Properties and from OperationsExecution

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Workspace RulesWs = 〈Ag,Ar ,Art ,Ev ,M,R, t〉

Needed to specify rules governing

intra-workspace dynamics

Workspace as aprogrammable entity

Event-Condition-Action (ECA) rules:“when ev in the context c apply a”• +ev : c→ a• ev ∈ Ev• c refers to observable states∈ Ar

• a refers to a set of workspaceoperators

WORKSPACELAWS ( R ) Ev Art M

LINK OPERATIONOPERATIONOBSERVABLE PROPERTY

ARTIFACT

AGENT

ACTIONPERCEPTION

Legend

WS OPERATOR

LINKWorkspace Kernel

CArtAgOWorkspace

Basic Workspace Operators:

(1) applyOp(arid ,opname [,Params])(2) applyLop(arid ,opname [,Params])(3) make(arid ,artn [,Params])(4) dispose(arid)(5) disable(arid [,agid ] {,opname})(6) enable(arid [,agid ] {,opname})(7) exclude(agid)(8) include(agid)

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Workspace RulesWs = 〈Ag,Ar ,Art ,Ev ,M,R, t〉

Needed to specify rules governing

intra-workspace dynamics

Workspace as aprogrammable entity

Event-Condition-Action (ECA) rules:“when ev in the context c apply a”• +ev : c→ a• ev ∈ Ev• c refers to observable states∈ Ar

• a refers to a set of workspaceoperators

WORKSPACELAWS ( R ) Ev Art M

LINK OPERATIONOPERATIONOBSERVABLE PROPERTY

ARTIFACT

AGENT

ACTIONPERCEPTION

Legend

WS OPERATOR

LINKWorkspace Kernel

CArtAgOWorkspace

Basic Workspace Operators:

(1) applyOp(arid ,opname [,Params])(2) applyLop(arid ,opname [,Params])(3) make(arid ,artn [,Params])(4) dispose(arid)(5) disable(arid [,agid ] {,opname})(6) enable(arid [,agid ] {,opname})(7) exclude(agid)(8) include(agid)

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Hospital Scenario: EMI

joinWorkspaceHospital

useDesk

bookVisit

useBillingMachine

pay

quitWorkspaceHospital

useTerminalsendBill

enterthe room

book the visit

visit

visitor scheme

observe

send fee

monitorscheme

mSanpayvisit

enforcement

sendbill

mRewdo thevisit

mVisit mVisit

mPaymPatient

exitmVisit mStaff

useTerminalsendFee

useSurgeryTablet

signPat

focusDesk,

BillingMachine

Doctorscheme

visit patient

mDoc

useSurgeryTablet

signDoc BillingMachine Terminal

sendBillpay

Desk

bookVisit

sendFee

SurgeryTablet

signDocsignPat

reservations

payments

ENVIRONMENTMANAGEMENTINFRASTRUCTURE

visitsHospitalWorkspace

visitorSch monitorSch

docSch

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Hospital Scenario: Count-as

Count-As RulesAn event occurring in the system may “count-as” an institutional eventand automatically update the organization

+join_req(Ag)-> make("visitorGroupBoard","OMI.GroupBoard",["moise/hospital.xml","visitGroup"]);

make("visitorSchBoard","OMI.SchemeBoard",["moise/hospital.xml","visitorSch"]);

apply("visitorGroupBoard",adoptRole(Ag, "patient"));

include(Ag).

+op_completed("visitorGroupBoard", _,adoptRole(Ag, "patient"))

-> apply("visitorSchBoard",commitMission(Ag, "mPat")).

+ws_leaved(Ag)-> apply("visitorGroupBoard",

leaveRole(Ag, "patient")).

+op_completed("BillingMachine",Ag, pay)

-> apply("visitorSchBoard",setGoalAchieved(Ag, pay_visit)).

+op_completed("Terminal",Ag, sendFee)

-> apply("monitorSchBoard",setGoalAchieved(Ag, send_fee)).

Figure: Example of count-as rules in the Hospital scenario.

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Conclusions

Hospital Scenario: Enact

Enact RulesOrganization may produce a control by enacting changes upon theenvironment (i.e., to promote equilibrium, avoid undesiderable states).

+signal("visitorGroupBoard",role_cardinality, visitor)

: true-> disable("Desk", bookVisit).

+signal("monitorSchBoard",goal_non_compliance,obligation(Ag,ngoa(monitorSch,mRew,send_bill),achieved(monitorSch,send_bill,Ag),TTF)

: true-> exclude(Ag).

Figure: Example of enact rules in the hospital scenario.

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Outline

1 Introduction

2 Objectives



5 Implementation

6 Conclusions

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Conclusions

An unifying approach to MAS programming

• Embodied Organization;

• No need for agents to bring about organizational notions;

• Environment infrastructures succeed to mediate between agentsand organizations;

• Global dynamics shaped on workspace events and transparentlyhandled by the system.

Limitations and Aspects we do not address (yet):

• Direct communication between agents (Agent-Agent interaction)through message passing (i.e. ACL) is not currently under thecontrol of the organization.

• Complex interaction patterns may result in many relationship to bespecified between E-O.

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Conclusions

An unifying approach to MAS programming

• Embodied Organization;

• No need for agents to bring about organizational notions;

• Environment infrastructures succeed to mediate between agentsand organizations;

• Global dynamics shaped on workspace events and transparentlyhandled by the system.

Limitations and Aspects we do not address (yet):

• Direct communication between agents (Agent-Agent interaction)through message passing (i.e. ACL) is not currently under thecontrol of the organization.

• Complex interaction patterns may result in many relationship to bespecified between E-O.

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Piunti, M.

Introduction

Objectives



Implementation

Conclusions

Perspectives

Ongoing and Furure Work:

• To generalize the mechanism of Workspace Laws and EmbodiedOrganization Rules defining a wide set of inter-system functionalrelations (i.e. access control, security);

• To provide a general framweork for integrated MAS development

Applications in future ICT:

• Any scenario integrating artificial agents, devices, humans in thesame application

• Future Internet, Cloud Computing

• Sociotechnical systems, pervasive computing

• Virtualization, Electronic Marketplaces, etc.

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Conclusions

Bibliography IBáez-Barranco, J.-A., Stratulat, T., and Ferber, J. (2006).A unified model for physical and social environments.In Environments for Multi-Agent Systems III, Third International Workshop(E4MAS 2006), volume 4389 of Lecture Notes in Computer Science, pages41–50. Springer.

Baldoni, M., Genovese, V., and van der Torre, L. (2008).Adding Organizations and Roles as primitives to the JADE framework.In Proc. of the 3rd International Workshop on Normative MAS.

Boissier, O., Hübner, J. F., and Sichman, J. S. (2006).Organization Oriented Programming: From Closed to Open Organizations.In Engineering Societies for Agent Worlds (ESAW-2006). Extended andRevised version in Lecture Notes in Computer Science LNCS series,Springer, pages 86–105.

Bordini, R. H., Hübner, J. F., and Wooldrige, M. (2007).Programming Multi-Agent Systems in AgentSpeak using Jason.Wiley Series in Agent Technology. John Wiley & Sons.

Campos, J., Lòopez-Sànchez, M., Rodrìguez-Aguilar, J. A., and Esteva, M.(2008).Formalising Situatedness and Adaptation in Electronic Institutions.In COIN-08, Proc.

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Bibliography II

Castelfranchi, C. (1998).Modeling Social Action for AI Agents.Artificial Intelligence, 103:157–182.

Coutinho, L. R., Sichman, J. S., and Boissier, O. (2009).Modeliling dimensions for agent organizations.In Dignum, V., editor, Handbook of Research on Multi-Agent Systems:Semantics and Dynamics of Organizational Models. IGI-Global.

Dastani, M. (2008).2APL: a practical agent programming language.Autonomous Agent and Multi-Agent Systems, 16:214–248.

Dastani, M., Grossi, D., Meyer, J.-J. C., and Tinnemeier, N. A. M. (2008).Normative Multi-Agent Programs and Their Logics.In Knowledge Representation for Agents and Multi-Agent Systems, FirstInternational Workshop, KRAMAS 2008, Sydney, Australia, Revised SelectedPapers, volume 5605 of Lecture Notes in Computer Science. Springer.

Dignum, M. V. F. d. A. J. G. (2003).A model for organizational interaction: based on agents, founded in logic.PhD thesis, Utrecht University, SIKS dissertation series 2004-1.

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Bibliography III

Dignum, V., editor (2009).Handbook of Research on Multi-Agent Systems: Semantics and Dynamicsof Organizational Models.IGI-Global.

Esteva, M., Rodríguez-Aguilar, J. A., Rosell, B., and L., J. (2004).AMELI: An agent-based middleware for electronic institutions.In Jennings, N. R., Sierra, C., Sonenberg, L., and Tambe, M., editors,Proceedings of International conference on Autonomous Agents and MultiAgent Systems (AAMAS’04), pages 236–243, New York. ACM.

Ferber, J., Gutknecht, O., and Michel, F. (2003).From Agents to Organizations: An Organizational View of Multi-agentSystems.In Proceedings of (AOSE-03), volume 2935 of Lecture Notes ComputerScience (LNCS). Springer.

Gasser, L. (2001).Perspectives on Organizations in Multi-agent Systems.In Multi-Agent Systems and Applications, volume Vol. 2086 of Lecture Notesin Computer Science, pages 1–16. Springer-Verlag New York, Inc., NewYork, NY, USA.

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Bibliography IV

Hübner, J. F., Boissier, O., Kitio, R., and Ricci, A. (2009).Instrumenting Multi-Agent Organisations with Organisational Artifacts andAgents.Journal of Autonomous Agents and Multi-Agent Systems.

Hübner, J. F., Sichman, J. S., and Boissier, O. (2005).S-moise+: A middleware for developing organised multi-agent systems.In Boissier, O., Padget, J. A., Dignum, V., Lindemann, G., Matson, E. T.,Ossowski, S., Sichman, J. S., and Vázquez-Salceda, J., editors,Coordination, Organizations, Institutions, and Norms in Multi-Agent Systems,AAMAS 2005 International Workshops, volume 3913 of Lecture Notes inComputer Science, pages 64–78. Springer.

Hübner, J. F., Sichman, J. S., and Boissier, O. (2007).Developing Organised Multi-Agent Systems Using the MOISE Model:Programming Issues at the System and Agent Levels.Agent-Oriented Software Engineering, 1(3/4):370–395.

Kirsh, D. (1995).The intelligent use of space.Artificial Intelligence, 73(1-2):31–68.

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Conclusions

Bibliography V

Okuyama, F. Y., Bordini, R. H., and da Rocha Costa, A. C. (2009).A distributed normative infrastructure for situated multi-agent organisations.In Declarative Agent Languages and Technologies VI, volume 5397 ofLecture Notes Computer Science (LNCS). Springer.

Omicini, A., Ricci, A., and Viroli, M. (2008).Artifacts in the A&A meta-model for multi-agent systems.Autonomous Agents and Multi-Agent Systems, 17 (3).

Piunti, M. and Ricci, A. (2008).From Agents to Artifacts Back and Forth: Purposive and Doxastic use ofArtifacts in MAS.In Proceedings of Sixth European Workshop on Multi-Agent Systems(EUMAS-08), Bath, UK.

Piunti, M., Ricci, A., Boissier, O., and Hübner, J. F. (2009a).Embodied Organisations in MAS Environments.In Braubach, L., van der Hoek, W., Petta, P., and Pokahr, A., editors, MATES,volume 5774 of Lecture Notes in Computer Science, pages 115–127.Springer.

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Bibliography VIPiunti, M., Ricci, A., Boissier, O., and Hübner, J. F. (2009b).Embodying Organisations in Multi-agent Work Environments.In Proceedings of the 2009 IEEE/WIC/ACM International Joint Conferenceon Web Intelligence and Intelligent Agent Technology (WI-IAT 2009), pages511–518, Milan, Italy. IEEE.

Piunti, M., Ricci, A., Braubach, L., and Pokahr, A. (2008).Goal-directed Interactions in Artifact-Based MAS: Jadex Agents playing inCArtAgO Environments.In IEEE/WIC/ACM International Joint Conference on Web Intelligence andIntelligent Agent Technology (WI-IAT 2008), Sydney, NSW, Australia.

Pokahr, A., Braubach, L., and Lamersdorf, W. (2005).Jadex: A BDI Reasoning Engine.In Bordini, R. H., Dastani, M., Dix, J., and Fallah-Seghrouchni, A. E., editors,Multi-Agent Programming, volume 15 of Multiagent Systems, ArtificialSocieties, and Simulated Organizations, pages 149–174. Springer.

Ricci, A., Piunti, M., Viroli, M., and Omicini, A. (2009).Environment programming in CArtAgO.In Bordini, R. H., Dastani, M., Dix, J., and El Fallah-Seghrouchni, A., editors,Multi-Agent Programming: Languages, Platforms and Applications, Vol. 2,pages 259–288. Springer.

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Bibliography VII

Searle, J. R. (1964).Speech Acts, chapter What is a Speech Act?Cambridge University Press.

Searle, J. R. (1997).The Construction of Social Reality.Free Press.

Stratulat, T., Ferber, J., and Tranier, J. (2009).MASQ: Towards an Integral Approach of Agent-Based Interaction.In Proc. of 8th Conf. on Agents and Multi Agent Systems (AAMAS-09).

Weyns, D., Omicini, A., and Odell, J. J. (2007).Environment as a first-class abstraction in multi-agent systems.Autonomous Agents and Multi-Agent Systems, 14(1):5–30.Special Issue on Environments for Multi-agent Systems.

Wooldridge, M. and Jennings, N. R. (1995).Intelligent agents: Theory and practice.The Knowledge Engineering Review, 10(2):115–152.

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Designing and ProgrammingOrganizational Infrastructures for Agentssituated in Artifact-based Environments

European PhD

Michele [email protected]

ALMA MATER STUDIORUMUniversità di Bologna – DEIS

Bologna

April 30th, 2010

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[email protected]




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Situated Organizations• MASQ, AGRE [Stratulat et al., 2009, Báez-Barranco et al., 2006]: integrate

different dimensions (agents, environment, interactions, organizations andinstitutions) into an integral view;

• Distributed normative infrastructures: “normative places” and “normativeobjects”, reactive entities inspectable by agents and containing readableinformation about norms [Okuyama et al., 2009].

• Situated Electronic Institutions [Campos et al., 2008]: governor entitiesallow to bridge environmental structures by instrumenting environments withembodied devices controlled by the institutional apparatus.

• Constitutive rules [Searle, 1997] to bridge the gap between environmentand institutional dimensions:

• The reification of a particular state in a normative place mayconstitute the realization of a particular institutional fact (e.g., “beingon a car driver seat makes an agent to play the role driver”)[Okuyama et al., 2009].

• “Normative artifact” as a container of institutional facts (facts related tothe institutional states), and brute facts (states related to the concreteworkplace where agents dwell) [Dastani et al., 2008]. “Count-as” and“sanctioning” rules allows the infrastructure to recast brute facts toinstitutional ones and provide normative control.

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Syntax of Workspace Rules

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Regimentation and Enforcement

mechanis

ms

Staff

Agent

Organisational

Artifacts

EOA+OA

used by

Regimentation

Enforcement

detection

evaluation

judgement

done by

done by

done by

done by

• Regimentation is done by enabling and disablingoperation controls (uic) on environment artifacts(visitDoor)

• This enables or prevents the use of artifacts (CArtAgOimplements RBAC)

• Enforcement is done (by staff/organizational agents) byusing special artifacts (i.e. the terminal to send fines,the phone to call police, etc.)

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PhD dissertation 2010

Technology

Transcript of PhD dissertation 2010