Multi agent systems chapter 2 adapted with permission from adina magda florea adina@wpi edu
1 / 41

Multi-Agent Systems Chapter 2 Adapted (with permission) from Adina Magda Florea [email protected] - PowerPoint PPT Presentation

  • Uploaded on

Multi-Agent Systems Chapter 2 Adapted (with permission) from Adina Magda Florea [email protected] Candy Quiz (not for points, just for candy). What do each of the following mean? KQML ACL Ontology Illocution KSE FIPA KIF. Candy Quiz (not for points, just for candy).

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about ' Multi-Agent Systems Chapter 2 Adapted (with permission) from Adina Magda Florea [email protected]' - alanna

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Multi agent systems chapter 2 adapted with permission from adina magda florea adina@wpi edu

Multi-Agent SystemsChapter 2Adapted (with permission) fromAdina Magda [email protected]

Candy quiz not for points just for candy
Candy Quiz(not for points, just for candy)

  • What do each of the following mean?

    • KQML

    • ACL

    • Ontology

    • Illocution

    • KSE

    • FIPA

    • KIF

Candy Quiz(not for points, just for candy)

  • What do each of the following mean?

    • KQML Knowledge Query Manipulation Language

    • ACL Agent Communication Language

    • Ontology specification of objects, concepts and relationship

    • Illocution intended meaning - performative

    • KSE Knowledge Sharing Efort

    • FIPA Foundation for Intelligent Physical Agents

    • KIF Knowledge Interchange Format

1 the nature of communication

Syntax-how structured

Semantics-symbol meaning


1. The nature of communication

Human communication

  • Communication is the intentional exchange of information brought about by the production and perception of signs drawn from a shared system of conventional signs (AIMA, Russell&Norvig) language

  • Communication seen as an action (communicative act) and as an intentional stance (want something to happen)

    Component steps of communication


     IntentionPerception

    Generation- createAnalysis

    Synthesis- organizeDisambiguation



Artificial Communication

  • low-level language vs high-level languages

  • direct communication vs. indirect communication

    Computer communication

  • shared memory message passing

    Agent communication/ MAS communication

  • Communication in MAS = more than simple communication, implies interaction

  • The environment provides a computational infrastructure where interactions among agents take place. The infrastructure includes protocols for agents to communicate and protocols for agents to interact


Communication protocols= enables agents to exchange and understand messages

Interaction protocols= enable agents to have conversations, i.e., structured exchanges of messages. Can trace series of responses.

Aim  Communication enables agents to:

  • coordinate their actions and behavior

  • attempt to change state of the other agents

  • attempt to get other agents perform actions


Communication infrastructure

blackboard (shared memory) or message-based

connected or connection-less (email)

point-to-point (1), multicast (some), broadcast (all)

push or pull (information given to you or requested)

synchronous or asynchronous

Dimensions of meaning think of examples of each
Dimensions of Meaning(think of examples of each)

  • Descriptive/Prescriptive: describe phenomenon vs proscribe behavior (I am cold)

  • Personal/conventional: different meaning to individual

  • Semantics/Pragmatics: interpreted differently than intended: mental states

  • Contextuality: cannot be understood in isolation

  • Coverage: language express necessary concepts

  • Identity: meaning is dependent on individual

  • Cardinality: private message interpreted differently than public message

2 indirect communication

Reactive agents


Agent A

(stimulus triggers

behavior P)

Agent B

(stimulus triggers

behavior P)

2. Indirect communication

2.1 Signal propagation - Manta, A. Drogoul 1993

  • An agent sends a signal, which is broadcast into the environment, and whose intensity decreases as the distance increases

  • At a point x, the signal may have one of the following intensities (why?)

    V(x)=V(x0)/dist(x,x0) V(x)=V(x0)/dist(x,x0)2


Topological differences

lead to social differences

2.2 Trails- L. Steels, 1995

agents drop "radioactive crumbs" making trails

an agent following a trail makes the trail faint until it disappears


Cognitive agents






2.3Blackboard systems, Barbara Hayes-Roth, 1985

  • Blackboard = a common area (shared memory) in which agents can exchange information, data, knowledge

  • Agents initiates communication by writing info on the blackboard

  • Agents are looking for new info, they may filter it

  • Agents must register with a central site for access authorization

  • Blackboard = a powerful distributed knowledge paradigm

  • Agents = Knowledge sources (KS)



Pending KS Activations


3 direct communication
3. Direct communication

Sending messages = method invocation

  • The Actor language

    • an Actor executes a sequence of actions in reply to the received message

  • Exchange of partial plans

    • distributed planning

      ACL = Agent Communication Languages

      communication as action - communicative acts



Content language


3.1 Agent Communication Languages

  • Concepts (distinguish ACLs from RPC, RMI or CORBA, ORB):

    • ACLs handle propositions, rules, and actions instead of objects with no associated semantics

    • An ACL message describes a desired state in a declarative language, rather than a procedure or method invocation

    • ACLs are mainly based on BDI theories: BDI agents attempt to communicate their BDI states or attempt to alter others BDI state

    • ACLs are based on Speech Act Theory

    • Agent behavior and strategy drive

      communication and lead to conversations


Ontology =formal definition of a body of knowledge. The most typical ontology used in building agents involves a structural component. Essentially a taxonomy of class and subclass relations coupled with definitions and relationships between things. (Jim Hendler)

An ontology is analogous to a data base organization, not the contents of the database.

Example: To express the idea that a block is a physical object we might use the FOPL expression:

x (Block x)  (PhysicalObject x)

To state relationships between classes:

x,y,z (instanceOf x y ) (subclassOf y z) (instanceOf x z)

To define a relationship On(X,Y)

(domain On PhysicalObject)

(range On PhysicalObject)

Origins of acls
Origins of ACLs

Knowledge Sharing Effort - DARPA, 1990

  • External Interface Group - interaction between KBS - KQML

  • Interlingua – language for communicating between independent agents. KIF (not designed as a language to be used by humans)

  • Shared, Reusable Knowledge Bases –

  • Ontolingua (set of tools written in Lisp for analyzing and translating ontologies. Uses KIF parser and syntax checker. Web-based)

Theory of Speech Acts

J. Austin - How to do things with words, 1962,

J. Searle - Speech acts, 1969

Treats communication as an action – made to further agent’s intentions

Changes world in a way analogous to physical actions

Need formal representation so planning systems can reason about them.

A speech act has 3 aspects:

  • locution = physical utterance by the speaker

  • illocution = the intended meaning of the utterance by the speaker (performative)

  • prelocution = the action that results from the locution

    Alice told Tom: "Would you pleaseclose the door“


Human communication intent may be ambiguous
Human Communication: Intent may be ambiguous

  • Colleague states “I am cold”

  • What is the meaning?

  • For computers, state performative (KQML) or Communicative Act (FIPA) so no ambiguity (except in content itself).

Illocutionary aspect - several categories

(According to speech act theory)

  • Assertives, which inform: the door is shut

  • Directives, which request: shut the door, can pelicans fly?

  • Commissives, which promise something: I will shut the door

  • Permissive, which gives permission for an act: you may shut the door

  • Prohibitives, which ban some act: do not shut the door

  • Declaratives, which causes events: I name you king of Cache Valley

  • Expressives, which express emotions and evaluations: I am happy




KQML – Knowledge Query and Manipulation Language

A high-level, message-oriented communication language and protocol for information exchange, independent of content syntax (KIF, SQL, Prolog,…) and application ontology

KQML separates:

  • semantics of the communication protocol (domain independent)

  • semantics of the message (domain dependent)

    3 (conceptual) layers

Core of KQML

- identity of the network protocol with which to deliver the message

- speech act or performative


- content language

- ontology

Describes low level

communication parameters:

- identity of sender and receiver

- a unique id associated with the communication




(tell :sender willie

:receiver joe

:reply-with block1

:language KIF

:ontology BlockWorld

:content (AND (Block A)(Block B)

(On A B)) )

Syntax LISP-like list of attribute/value pairs

(ask-one :sender joe

:receiver ibm-stock

:reply-with ibm-stock

:language PROLOG // of content

:ontology NYSE-TICKS // define terminology

:content (price ibm ?price) )

1. Query performatives: ask-one, ask-all (want all answers to question), ask-if, stream-all (multiple response version of ask-all)





(stream-all :sender willie

:receiver ibm-stock

:content (price ?VL ?price ) )


:content (stream-all

:content (price ?VL ?price) )














2. Generator performatives:

standby (be ready to respond), ready, next, rest, discard, generate,...

3. Response performatives:

reply, sorry ...



4. Generic informational performatives:

tell (I know it), untell,

insert (add to your VKB), delete, ...

5. Capability performatives:

advertise, subscribe, recommend...



6. Network performatives:

register, unregister, forward, route, ...



Knowledge sharing effort kse
Knowledge Sharing Effort KSE

  • Darpa funded in 1990

  • Resulted in

    • KQML

    • KIF (knowledge interchange format) looks like first order logic (and, or, forall, exists) cast into Lisp-like notation

      • Used for content part of KQML message

Example of kqml dialog
Example of KQML Dialog

(evaluate :sender A :receiver B :language KIF :ontology motors

:reply-with q1

:content (val (torque m1))


:sender B :receiver A :language KIF

:ontology motors :in-reply-to q1

:content (= (torque m1) (scalar 12 kgf))

Another example of kqml
Another example of KQML

(stream-about // multiple responses wanted

:sender A :receiver B :language KIF :ontology motors

:reply-with q1 :content m1)

(tell :sender B :receiver A :in-reply-to q1

:content (=(torque m1) (scalar 12 kgf))

(tell :sender B :receiver A :in=reply-to q1

:content (= (status m1) normal))

(eos :sender B :receiver B :in-reply-to q1)//end of stream

In the next kqml example
In the next KQML example

  • A advertises that it is willing to accept subscriptions related to m1.

  • B responds by subscribing

  • A sends message sequence about m1

  • A untells the previous fact and gives new information

  • eos ends the stream of messages

(advertise :sender A :language KQML :ontology K10

:content (stream-about :language KIF

:ontology motors :content m1)))

(subscribe :sender B :receiver A :reply-with s1

:content (stream-about :language KIF :ontology

motors : content m1))

(tell :sender A :receiver B :in-reply-to s1

:content (=(torque m1)(scalar 12 kgf)))

(tell :sender A :receiver B :in-reply-to s1

:content (=(status m1) normal))

(untell :sender A :receiver B :in-reply-to s1

:content (=(torque m1)(scalar 12 kgf)))

(tell :sender A :receiver B :in-reply-to s1

:content (=(torque m1)(scalar 15 kgf)))

(eos :sender A :receiver B :in-reply-to s1)













Facilitator agent

= an agent that performs various useful communication services:

  • maintaining a registry of service names (Agent Name Server)

  • forwarding messages to named services

  • routing messages based on content

  • matchmaking between information providers and clients

  • providing mediation and translation services









A wants to get all suitable

agents to respond to ask(P).

B has told F it can do

ask(P). F tells B to tell A




Semantics of KQML (Labrou & Finin)

Use preconditions and post conditions that govern the use of a performative + the final state for the successful performance of the performative

Uses propositional attitudes: belief Bel(A,P), knowledge Know(A,S),

desire Want(A,S), intentions Int(A,S)

Preconditions: the necessary states for an agent to send a performative and for the receiver to accept it and successfully process it; if the preconditions do not hold, the most likely response is error or sorry

Postconditions - describe the state of the sender after successful utterance of a performative and of the receiver after the receipt and processing of a message

Completion condition - the final state after a conversation has taken place and that the intention (associated with the performative that started the conversation) has been fulfilled



A states to B that A believes the content X to be true, Bel(A,X)

Pre(A): Bel(A,X)  Know(A, Want(B, Know(B,S))) no unsolicited info

Pre(B): Int(B, Know(B,S))

where S may be any of Bel(B,X) or Bel(B,X)

Post(A): Know(A, Know(B, Bel(A,X)))

Post(B): Know(B, Bel(A,X))

Completion: Know(B, Bel(A,X))


A states to B that A can and will process the message M from B, if it receives one

commisive act

Pre(A): Int(Proc(A,M))

Pre(B): NONE

Post(A): Know(A, Know(B, Int(A, Proc(A,M)))

Post(B): Know(B, Int(A, Proc(A,M)))

Completion: Know(B, Int(A, Proc(A,M)


Criticisms of kqml
Criticisms of KQML

  • not fixed performatives – different implementations don’t interoperate

  • transport mechanisms (ways of getting a message from A to B) not precisely defined

  • semantics not rigorous – not adhered to

  • missing commissives (make commitment)

  • performative set too large and ad hoc

    Resulted in FIPA


Foundation for Intelligent Physical Agents, 1996

Goal of FIPA = make available specifications that maximize interoperability across agent-based systems. SL formal language

Syntax similar to KQML

(inform :sender Agent1

:receiver Agent2

:content (price good2150)

:in-reply-to round-1

: reply-with bid03

: language S1

:ontology hp-auction

:reply-by 10

:protocol offer

:conversation-id conv-1 )

FIPA communicative acts


- query_if, subscribe, inform, inform_if

confirm, disconfirm, not_understood

Task distribution

- request, request_whenever, cancel, agree,

refuse, failure


- cfp (call for proposal - initiate), propose,

accept_proposal, reject_proposal


FIPA - Semantics

SL (Semantic Language) - a quantified, multi-modal logic, with modal operators:

B - belief

D - desire

U - uncertain belief – neither believes  or its negatation, but believes  more

likely than its negation.

PG - persistent goal, but will not necessarily plan to bring it about

Bif - agent believes  or disbelieves 

Uif - agent has an uncertain belief of  or an uncertain belief of ¬ 

Given that one of the most frequent and serious criticisms of KQML is the lack of adequate semantics, it is not surprising that the developers of FIPA felt it important to give comprehensive formal semantics to their language.


The semantics of a communicative act is specified as a set of SL's formulae that describe:

Feasibility preconditions - the necessary conditions for the sender - the sender is not obliged to perform the CA

Rational effect - the effect that an agent can expect as a result of performing the action; it also typically specifies conditions that should hold true of the recipient

The receiving agent is not required to ensure that the expected effect comes about

The sender can not assume that the rational effect will necessary follow

Semantics of inform:

<i, inform(j, )>

Pre: Bi  Bi (Bifj  Uifj)

Post: Bj 

Syntax of request: of SL's formulae that describe:

<k, request(j, )>

Pre: BkAgent( ,j)   BkIj(Done )

Post: Done()

Agent( ,j) means that the agent of action  is j (j is the one who can perform the action)

Done( ) means that the action has been done

Effect: agent k is requesting agent j to do action  and agent k believes that the agent to do the action is j and it believes that j does not currently intend to do the action. The effect is that j will do it.

Using ACLs in MAS of SL's formulae that describe:

Any MAS that is to use an ACL must provide:

  • a finite set of APIs for composition, sending, and receiving ACL messages

  • an infrastructure of services that assist agents in naming, registration, and basic facilitation services (finding other agents that can do things for your agent)

  • code for every reserved message type that takes the action prescribed by the semantics for the particular application;

  • the code depends on the application language, the domain, and the details of the agent system using the ACL


  • History of DAML (one possible content language) of SL's formulae that describe:

    • HTML defines grammar for interspersing documents with markup commands.

    • HTML is fixed – can’t introduce tags

    • Suppose you want to sell CDs and put price information on the web.

    • HTML can markup with layout information, but browsers won’t know how to interpret content. What is price? What is title?

    • XML was developed to provide semantic markup – helps computers to process information in document by allowing user defined tags.

    • DAML (Darpa markup language) is based on XML

4 communication content

ACL of SL's formulae that describe:

Content language


4. Communication content

  • Content languages

    • KIF

    • Prolog

    • Clips

    • SQL


    • DAML

    • XML Xtensible Markup Language

  • Ontologies

DARPA Agent Markup Language

The DAML Program officially began in August 2000.

The goal of the DAML effort is to develop a language

and tools to facilitate the concept of the Semantic Web.


Interaction protocols of SL's formulae that describe:

enable agents to have conversations, i.e., structured exchanges of messages

  • Finite automata

  • Conversations in KQML

  • Petri nets - more in distributed planning lecture

  • FIPA IP standards:

    • FIPA-query,FIPA-request,FIPA-contract-net,

Finite state automata nodes represent states arrows represent actions
Finite state automata of SL's formulae that describe:Nodes represent statesArrows represent actions

COOL, Barbuceanu,95

A:B<<ask(do P)

B:A<<accept(do P)


B:A<<refuse(do P)



B:A<<fail(do P)

B:A<<result(do P)



Winograd, Flores, 1986




Conversations in KQML of SL's formulae that describe:

Use Definite Clause Grammars (DCG) formalism for the specification of conversation policies for KQML performatives

DCGs extend Context Free Grammars in the following way:

  • non-terminals may be compound terms

  • the body of the rule may contain procedural attachments, written as "{" and "}" that express extra conditions that must be satisfied for the rule to be valid

    Ex: noun(N)  [W], {RootForm(W,N), is_noun(N)}

    S  s(Conv, P, S, R, inR, Rw, IO, Content), {member(P, [advertise, ask-if]}

    s(Conv, ask-if, S, R, inR, Rw, IO, Content) 

    [ask-if, S, R, inR, Rw, IO, Content] |

    [ask-if, S, R, inR, Rw, IO, Content], {OI is inv(IO)},

    r(Conv, ask-if, S, R, _, Rw, OI, Content)

    r(Conv, ask-if, R, S, _, inR, IO, Content) 

    [tell, S, R, inR, Rw, IO, Content] |

    problem(Conv, R, S, inR, _, IO)

Labrou, Finin, 1998


DA of SL's formulae that describe:





Petri nets

Ferber, 1997

Petri net = oriented graph with 2 type of nodes:places and transitions;

there are moving tokens through the net - representation of dynamic aspect of processes.

Stores state.

Tokens are moved from place to place, following firing rules.

A transition T is enabled if all the input places P of T contains a token

A marking (state) is a distribution of tokens over places.

B does not want

to do(P)

A wants to do P,

A cannot do P

B is willing

to do(P)

Request do(P)

Refuse do(P)

Accept/request do(P)


Fail to do(P)


to do(P)

Notification of end(P)







References of SL's formulae that describe:

M. Huhns, L. Stephens. Multiagent systems and societies of agents. In Multiagent Systems - A Modern Approach to Distributed Artificial Intelligence, G. Weiss (Ed.), The MIT Press, 2001, p.79-120.

M. Wooldrige. Reasoning about Rational Agents. The MIT Press, 2000, Chapter 7

Y. Labrou, T. Finin. Semantics and conversations for an agent communication language. In Readings in Agents, M. Huhns & M. Singh (Eds.), Morgan Kaufmann, 1998, p.235-242.

J. Ferber - Multi-Agent Systems. Addison-Wesley, 1999, Chapter 6

T. Finnin, R. Fritzson - KQML as an agent communication language. In Proc. of the Third International Conference on Information and Knowledge Management (CIKM'94), ACM Press, 1994.

M. Singh. Agent communication languages: Rethinking the principles. IEEE Computer, Dec. 1998, p.40-47.

Y. Labrou, T. Finnin, Y. Peng. Agent communication languages: The current Landscape. IEEE Computer, March/April 1999, p. 45-52.

FIPA97. "Agent Communication Language" Specification FIPA, 11/28/97