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.