ESAW 2004

ExtendingElectronic Institutions:

An Explorer’s Log

Pablo Noriega

IIIA-CSIC

Barcelona

EUMAS 04

Barcelona

December 16,17

REGISTER SOON

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Goals of this Talk

• Present the underlying intuitions of our proposals

• Share our present cogitations

• Invite you to participate

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EI gang at IIIA-CSIC

Currently:Josep Lluis Arcos* Eva Bou* Guifre Cuni* Andres GarciaPere Garcia * Andrea Giovanucci* Carlos HernandezPablo NoriegaJuan Antonio Rodriguez AguilarMarco SchloemererCarles Sierra

Formerly:Mark EstevaJordi Sabater

http://e-institutions.iiia.csic.es/

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EI-Influencias

Dialogues

Economics

Norms

Coordination

MASMASMASMAS

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“Institution: collection of artificial constraints that regulate agent interactions”

A.D. North

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EI and ordinary institutions

• Fix meaning

• Clarify expectations on the behavior of others

• Implement due process

• Interface:

Individual rationality and social outcomes

Purpose: reduce uncertainty

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EI : alternative views

• EIs as Dialogues:• Dialogical language• Types of dialogue (protocol, point of conversation)• Changes of conversation• Obligations

• EIs as Norms• Logical theories• Context• Compliance / enforcement

• EIs as Interface:• Coordination artifact• Interaction-centered problem solving• Success / failure

Computational Environments

Applications

Social Perspective

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Adscription

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A-open MAS

Definition: An Adscription-open SystemAdscription-open System is a distributed system involving autonomous, independent entities that are willing to conform to a shared set of interaction conventions

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A-open MAS: H0

• Participants are commitment-making agents

• All interactions are construable as speech acts

• Interactions are repetitive

• Interactions produce social commitments

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EI = I(H0)

Dialogical Framework: Linguistic and social structure to give meaning to agent interactions.

Performative Structure: scenes and relationships between scenes (navigation, precedence, causality)

Rules: Role-dependent conventions to establish social commitments

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Electronic Institution Components

PERFORMATIVE STRUCTURE

(NETWORK OF PROTOCOLS)SCENE

(MULTI-AGENT PROTOCOL)

AGENT ROLES

Buyers’ Payment

NORMS

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Simple Electronic Institutions: EI0 = I0(I(H0))

Dialogical Framework: Linguistic and social structure to give meaning to agent interactions.

Performative Structure: scenes and relationships between scenes (navigation, precedence, causality)

Rules: Role-dependent conventions to establish social commitments

DF = <O, I, L, RI, RE, RS>

S = <Rs ,DFs ,W,w0,Wf,(WAr)r R ,(WEr)r R ,,,min,Max >

PS = < S,T,s0,s ,E,fL,fT,fEO,C, >

(nj =1uttered(sj,wkj,ilj) m

k=1ek)(n’j=1uttered(s’j,w’kj,i’lj) m’

k = 0 e’ k )

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EI0: Dialogical Framework

• We define a dialogical framework as a tuple DF = <O, I, L, RI, RE, RS> where:

• O stands for the institutional ontology;

• I is the set of illocutionary particles;

• L stands for a representation language;

• RI is the set of internal roles;

• RE is the set of external roles; and

• RS is the list of relationships over roles;

Illocution: i (, , )

Declare (auct,all, offer(good,price), t)

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Performative Structure

• Complex activities can be specified by establishing relationships among scenes that:

• capture causal dependency.

• define synchronisation mechanisms.

• establish parallelism mechanisms.

• define choice points that allow roles leaving a scene to choose which activity to engage in next.

• establish the role flow policy.

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Sellers’ admission

Buyers’admission

FM Scenes

Bidding

Sellers’ settlements

Buyers’ settlements& Delivery

Buyers Sellers

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EI0: Performative Structure• A performative structure is a tuple

PS = < S,T,s0,s ,E,fL,fT,fEO,C, > where:

• S is a finite, non-empty set of scenes;• T is a finite and non-empty set of transitions;

• s0 S is the root scene;

• s S is the output scene;• E = EI EO is a set of arc identifiers where EI S x T is a set

of edges from scenes to transitions and EO T x S is a set of edges from transitions to scenes;

• fL: E 2VA x R is the labelling function;

• fT: T {AND-AND,AND-OR,OR-OR,OR-AND} maps each transition to its type;

• fEO: EO E maps each arc to its type;

• C: EI CONS maps each arc to a boolean expression representing the arc's constraints.

: S {0,1} sets if a scene can be multiply instantiated at execution time

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FM Performative Structure (ISLANDER)

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Scene

• A scene is a pattern of multi-agent conversation.• A scene is specified by a finite state oriented graph

where the nodes represent the different states and oriented arcs are labelled with illocution schemes or timeouts.

• During the enactment new agents can join the scene or some of the participants can leave the scene at definite states depending on their role.

• A scene may have multiple (simultaneous) instantiations, and be enacted by different groups of agents.

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Voice Bidding

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EI0: SceneFormally, a scene is a tuple:

S = <R,DF,W,w0,Wf,(WAr)r R,(WEr)r R,,,min,Max >

where:• R is the set of roles of the scene;• DF is a dialogical framework;• W is a finite, non-empty set of scene states;

• w0 W is the initial state;

• Wf W is the non-empty set of final states;

• (WAr)r R W is a family of non-empty sets such that WAr stands for the set of access states for the role r R;

• (WEr)r R W is a family of non-empty sets such that WEr stands for the set of exit states for the role r R;

W x W is a set of directed edges; : L is a labelling function;• min,Max: R N min(r) and Max(r) return respectively the

minimum and maximum number of agents that must and can play the role r R

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Norms

• Social Committments

• Illocutionary meaning

• Individual Navigation

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EI0: NormsIndividual behavior rules define the conditions for an agent

to take an action and the effects of taking such actions within the institution.

• Conditions:• Current state of the scene (conversation)

• Role played by speaker and hearers of a given illocution

• Prevailing state of social commitments

• Effects:• Changes in the state of a conversation and social commitments

• Obligations imposed to agents.

• Trajectories that agents can follow.

Example

A buyer winning a bidding round is required to proceed to the buyers settlement scene to pay for the good.

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FM: Individual Behavior Rules

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EI0 Norm Enforcement device: Governor

• Agent whose purpose is to mediate between the institution and participating agents.

• Each external agent is attached to a governor that sees to it that the agent behaves according to the institutional conventions:

• IDENTITY

• NAVIGATION

• INFORMATION PASSING

• MESSAGES

• TIMING

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EI: An Idealized Trajectory

FM-TestBed

FishMarket

AuctionsMASFIT

FM

EIEI0

ISLANDER

EIDE:ISLANDERSimdeiAMELIAbuilder

SADDESADDE

SADDESADDE

EIDE:ISLANDERSimdeiAMELIAbuilder

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EI0: Tools

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EI: Potential Development

EI EI0

Theory

Methodology

Applications

Tools

EIplus

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EI0: Cogitations

• We have taken a strong “dialogical stance”

• We have also dealt with static scene definitions

• We have taken a “policing” approach to norm compliance, and norm enforcement (so far).

• Integrated framework: representation / methodology / tools

• Unified metaphor from Design to deployment

• Applicable

• Extend to

• dynamic protocols and less structured interactions.

• other normative conceptions

• complex regulated social environments

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EI: Extensions

EI EI0

Theory

Methodology

Applications

Tools

EIplus

STRUCTURAL EXTENSIONS

NORMATIVE EXTENSIONS

META INSTITUTIONAL EXTENSIONS

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EI: Structural Extensions (1)

DB

UBCB

Vickrey

Auction PS

Scene Interchange

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EI: Structural Extensions (2)

UBCB

PS Splicing

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Splicing

• Splicing Techniques• Clipping

• Chopping

• Interleaving

• Growing

• Nesting

• Splicing Algebra ?• atomic operations

• separability,

• correctness,

• commitment consistency, …

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Revising Scenes

• Scenes as Functors

auction (<Protocol, parameters>;<Good-type>)

• Scenes as Goals

Price-fixing {fixed,auction,clearing,negotiation}

• PS as Problem Decomposition

AuctHouse:=registration + adminsion +

price-fixing + settlements

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Structural Extensions: Taxonomy Scene PS

Fixed with flexible parameters Fixed

STATIC

FLEXIBLE

Interchangeable from set of available fixed scenes

Fixed

DYNAMIC

FixedInterchangeable from set of

Available fixed PSs

FlexibleAssemblable from available

subPSc

O

P

E

N

Dialogical Patterns

Ag1 Ag2 Agn

Destination Data

I Ir12

I

I

INPUT

Output

CompetivnessPositioningSusteinabilityProfit

Scenarios

r2n

r1n

I = Institution

Agn= Agent “n”

ri n= Relationship Agi y Agn

Touring Machine

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EI: Meta-institutional Environments

$

?

Contr

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EI: Other Extensions

EIenvr

EI EI0 EI1

Theory

Methodology

Tools

EI2 EI

From “buildings” to “urbanism”

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Other Extensions: Taxonomy (2)

• Promulgation• External, Internal

• Compliance• Obligatory

• Facultative

• Enforcement• Strict

• Sanctions

• Self-enforced

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Id Promulgation PS Structure Compliance Enforcement

EI0

External Fixed Obligatory Strict

e-commerce

EIn

External Flexible Facultative Sanctions

e-government proceduresExternal & internal Evolving Facultative Incentives

Complaints, conflict resolution

EI

Internal Flexible Obligatory Self

Parlamentary Procedures

EIenv

External / internal Flexible Facultative Incentives

Tourism Destination

Supply Network

Extensions: Application Domain Examples

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EI Extensions

Applications

• EI0

e-commerce

• EIn

Due process

• EIAdscription open interactions

• EIenv

(Meta Institutional Environments)• Supply networks

• Localities

Tools

• e0

ISLANDER, AMELIE,…

• en

ISLANDER+, AMELIE+,…

• e

ISLANDER*,AMELI*…

Engineering Environments

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Ongoing Work

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Ongoing Work

http://e-institutions.iiia.csic.es

FREE CD and Demo

QUESTIONS?

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FIN

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BACKUP SLIDES

Juan Antonio Rodriguez, Marc Esteva, Josep Lluis Arcos,Et .al.

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EI adscription-open MAS

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EI adscription-open MAS

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Electronic Institution Infrastructure

JADE

Agent 1

CommunicationLayer

AutonomousAgents Layer

. . . Agent n

AMELI

JADE

Agent 1

CommunicationLayer

AutonomousAgents Layer

. . . Agent n

ElectronicInstitution

(Islander Spec)

TRADITIONAL APPROACH INSTITUTIONAL APPROACH

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AMELI functionalities

• MEDIATION• To facilitate agent communication within conversations (scenes).

• COORDINATION AND ENFORCEMENT• To guarantee the correct evolution of each conversation (preventing

errors made by the participating agents by filtering erroneous illocutions, thus protecting the institution).

• To guarantee that agents’ movements between scenes comply with the specification.

• To control which obligations participating agents acquire and fulfil.

• INFORMATION MANAGEMENT• To facilitate participating agents the information they need to

participate in the institution.

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Communication Layer

S M1...

...

Social layer(AMELI)

ParticipatingAgents Layer

InstitutionSpecification

(XMLformat)

-

...

...

S MmI M T M1 T Mk

G1 Gn

...

Gi

AiA1 An

-

Public

Private

... ...

AMELI architecture

INSTITUTIONMANAGER

SCENEMANAGERS

TRANSITIONMANAGERS

GOVERNORS

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Governor

• Mediates between institution and participating agent.

• Controls that an agent behaves according to the institution specification (rules).

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AMELI implementation features

• Agent-based

• Realised as a middleware layer

• Architecturally neutral

• General purpose (can interpret any institution specification)

• Communication neutral

• Scalable (it can be distributed among several machines)

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Operations

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Operations

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Operations

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Operations

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Operations

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Conclusions

• Engineering open multi-agent systems is a highly complex task.

• Electronic institutions reduce this complexity by introducing regulatory environments.

• We have presented AMELI, a social middleware that facilitates the deployment of electronic institutions.

• Given any institution specification, our social middleware is capable of enforcing the institutional rules.

• The combination of ISLANDER and AMELI targeted at supporting environment engineering in open multi-agent systems.

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Transition Management

• Movements are done asynchronously.

• For movements to current scene executions the transition informs the scene managers.

• For movements to new scene execution the transition manager informs the institution manager, which creates a scene manager for it.

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Transition management

• Each transition is managed by a transition manager.

• Agents within a transition can ask for target scenes to join.

• The transition manager is in charge of controlling when the transition can be fired (agents can move).

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Norm Management

• Java Expert System Shell (JESS) to manage norms.

• A governor has one thread devoted to manage its connection to JESS.

• For each norm Ni, this thread adds the corresponding R1i into the JESS rule base.

• Later on this thread adds the illocutions (appearing on the norms) as the facts of the system.

• JESS informs the thread whenever a rule is fired.

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Norm management

• Norms managed as a rule-based system.

• Constructed from an ISLANDER specification.

• The facts are illocutions uttered by agents.

• Each governor manages his agent’s obligations.

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Norm Management

A norm Ni :

is transformed into:

Antecedent

Defeasible

AntecedentObligations

Norm

Activation

Obligations

fulfilment

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Agent to Governor Messages

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Governor to Agent Messages

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Electronic Institution Specification with ISLANDER

Common Ontology and

language Agent Roles Multi-agent protocols Network of protocols Norms

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Institution Execution

• Electronic institutions will be populated at execution time by heterogenous and self-interested agents.

• The institution execution can be regarded as the execution of its different scenes.

• Agents devote their time:• interacting with other agents in the different scene executions

• moving among them.

• As a consequence agents acquire and fulfill obligations.

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Institution execution

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Institution execution

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Institution execution

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Approach

ENVIRONMENT

ENVIRONMENT

ELECTRONIC

INSTITUTION

NORMS

AGENT1

AGENT2

AGENT3

AGENT1

AGENT2

AGENT3

EXECUTION STATE:

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Approach

ENVIRONMENT

ENVIRONMENT

ELECTRONIC

INSTITUTION

NORMS

AGENT1

AGENT2

AGENT3

AGENT1

AGENT2

AGENT3

ActionCorrect?

EXECUTION STATE:

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Approach

ENVIRONMENT

ENVIRONMENT

ELECTRONIC

INSTITUTION

NORMS

AGENT1

AGENT2

AGENT3

AGENT1

AGENT2

AGENT3

’

EXECUTION STATE: → ’

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Execution State

= <Ag, , T, Obl> stands for an institution execution state where:

• Ag = {ag1, ..., agn} is a finite set of participating agents.

= { ik | si S, k N} is the set of all scene executions.

• T = {T1, ..., Tn} stands for all transition executions.

• Obl {obl1, ..., obln} is the set of agents’ pending obligations.

ik = {, , A} stands for scene execution state where: represents the scene’s current state.

= {1,..., n} stands for the context (bindings) produced by illocutions.

• A = {(ag,r) | ag Ag, r R} is the set participating agents along with their roles.

• Each transition execution state Ti = { (ag, ) | ag Ag, = { (ik, r) | i

k , r R}} contains agents’ target scenes.