Agent Communications Necessity Communication languages

Agent Communications • Necessity • Communication languages • Communication architectures

Motivation for Agent Communication ”Language is a very difficult thing to put into words” – Voltaire 1. Communication is required for cooperation between agents 2. Societies can perform tasks no individual agent can 3. Communicating agents need only know a ”common language” 4. Supports heterogenous agents

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 Component steps of communication Speaker Hearer Intention Generation Synthesis Syntax Perception Semantics Analysis Pragmatics Disambiguation Incorporation 3

Artificial Communication in a multi-agents system 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 4

ACL • Agent Communication Language (ACL) is based on speech-act theory. • Speech Acts. . . speaking a language is performing speech acts, acts such as making statements, giving commands, asking questions, making promises, and so on. - John Searle

Speech Acts • Speech act theories are pragmatic theories of language, i. e. , theories of language use: they attempt to account for how language is used by people every day to achieve their goals and intentions • The origin of speech act theories are usually traced to Austin’s 1962 book, How to Do Things with Words

Theory of Speech Acts J. Austin - How to do things with words, 1962, J. Searle - Speech acts, 1969 A speech act has 3 aspects: § locution = physical utterance(発話) 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 please close the door" locution illocution content prelocution: door closed (hopefully!) Illocutionary aspect - several categories o Assertives, which inform: the door is shut o Directives, which request: shut the door, can pelicans fly? o Commissives, which promise something: I will shut the door o Permissive, which gives permission for an act: you may shut the door o Prohibitives, which ban some act: do not shut the door o Declaratives, which causes events: I name you king of Ruritania o Expressives, which express emotions and evaluations: I am happy 7

The Speech Act Model An utterance is a spoken word or string of spoken words. At the simplest level, to utter is simply to say a word with no particular forethought or intention to communicate a meaning. Propositional Utterance is a more meaningful type of utterance makes reference to or describes a real or imaginary object. An illocutionary utterance is spoken with the intention of providing information, soliciting answers to questions, giving praise, and so on Perlocutionary utterances, on the other hand, do attempt to effect a change.

ACLs – communication as action - communicative acts - standard formats for the exchange of messages

KQML and KIF • The best known ACL is KQML, developed by the ARPA knowledge sharing initiative KQML is comprised of two parts: – the knowledge query and manipulation language (KQML) – the knowledge interchange format (KIF)

KQML • KQML is an ‘outer’ language, that defines various acceptable ‘communicative verbs’, or performatives Example performatives: – ask-if (‘is it true that. . . ’) – perform (‘please perform the following action. . . ’) – tell (‘it is true that. . . ’) – reply (‘the answer is. . . ’)

Categories of KQML performatives 1. 2. 3. 4. 5. 6. 7. Basic Query performatives Multi-response query performatives Response performatives Generic Informational performatives Generator performatives Capability performatives Networking performatives

1. Query performatives: ask-one, ask-all, ask-if, stream-all, . . . (ask-one : sender joe (tell : sender willie : receiver ibm-stock : receiver joe : reply-with ibm-stock : reply-with block 1 : language PROLOG : language KIF : ontology NYSE-TICKS : ontology Block. World : content (price ibm ? price) ) : content (AND (Block A)(Block B) (stream-all : sender willie : receiver ibm-stock : content (price ? VL ? price ) ) (standby : content (stream-all A : content (price ? VL ? price) ) stream-all(P) A tell(P 1) tell(P 2) eos A B (On A B)) ) ask-all(P) ask-one(P) B tell(P) tell(P 1, P 2, . . . ) B 13

2. Generator performatives: standby, ready, next, rest, discard, generate, . . . 3. Response performatives: reply, sorry. . . insert(P) A 4. Generic informational performatives: tell, untell, insert, delete, . . . 5. Capability performatives: advartise, subscribe, recommend. . . delete(P) B tell(P) A untell(P) B 6. Network performatives: register, unregister, forward, route, . . . Facilitator In fact, KQML contains only 2 types of illocutionary acts: assertives and directives + facilitator and network-related performatives (no necessarily speech acts) 14

Facilitator agent = an agent that performs various useful communication services: k maintaining a registry of service names (Agent Name Server) k forwarding messages to named services k routing messages based on content ask(P) k matchmaking between information providers and clients k providing mediation and translation services A tell(P) subscribe(ask(P)) A B tell(P) B recommend(ask(P)) advertise(ask(P)) reply(B) recruit(ask(P)) advertise(ask(P)) ask(P) A B tell(P) A ask(P) B tell(P) 15

KQML Examples I A B - (tell (> 3 2)) A B - (perform (print ”hello” t)) B A – (reply done) A B - (ask-if (> (size chip 1) (size chip 2) )) B A – (reply true) A B - (subscribe (position ? x ? r ? c)) B A – (tell (position chip 1 8 10)) B A – (tell (position chip 2 8 46)) B A – (tell (position chip 3 3 64)) A B - (unsubscribe (position ? x ? r ? c))

KQML Examples II (ask-one : content (geoloc TRD (? long ? lat)) : ontology geo-model 3) (ask-all : content ”price(IBM, [? price, ? time])” : receiver stock-server : language standard-prolog : ontology NYSE-TICS)

KIF – Knowledge Interchange Format KIF is a language for expressing message content Used to state: • Properties of things in a domain (e. g. , “Noam is chairman”) • Relationships between things in a domain (e. g. , “Amnon is Yael’s boss”) • General properties of a domain (e. g. , “All students are registered for at least one course”)

KIF examples - I Terms: (size chip 1) (+ (sin theta)(cos theta)) (if (> theta 0) theta (-theta)) (setofall ? x (above ? x chip 1)) Sentences: (Prime 565762761) (> (sin theta) (cos phi)) (not (> (sin theta) 0))) (> (* (width chip 1) (length chip 2))(*(width chip 1)(length chip 2))) (=> (> ? x 0) (positive ? x))

KIF Examples - II Definitions: (defrelation leq(? x ? y) : = (not (> ? x ? y))) (defrelation natural(? x) : = (and (integer ? x) (>= ? x 0))) Procedures: (progn (fresh_line t)(print ”Hi!”)(fresh_line t)) Meta-Knowledge: (believes John ’(material moon jarlsberg)) (=> (believes John ? p) (believes Mary ? p)) Rules: (<<= (flies ? x)(bird ? x))

KQML Statement Structure • KQML Statements consists of 1. A performative 2. Parameters and context information General syntax: (KQML-performative : sender word : receiver word : language word : ontology word : content expression. . . ) • A formal specification of a set of terms is known as an ontology • The knowledge sharing effort has associated with it a large effort at defining common ontologies 　- software tools like ontolingua

Ontologies Person Ontology = a specification of objects, concepts, and reationships in a particular domain; it comprises a Empl Stud Pupil vocabulary, a domain theory and a conceptual schemata to describe organization and interpretation IBM_E Sun_E An ontology is more than a taxonomy of classes, it must also describe relationships Joe Alice x (Block x) (Physical. Object x) Instead of (Block A) (Instance. Of A Block) (Class Block) Hierarchy (Class Physical. Objects) (Subclass. Of Block Physical. Objects) x, y, z (Instance. Of x y) (Subclass. Of y z) (Instance. Of x z) Ontology editors frame-based KR systems that allow the user to define an ontology and its components: classes, instances, relationships, and functions Person Man Empl Joe Woman Stud Alice 22

KQML Agent naming • System for mapping agents into names is important in most ACLs KQML assumes that names are local • – – • • A can register with B under the name Alice A can register with C under the name Albert Doesn’t preclude the use of a central Agent Name Server, an architecture used by most systems What gets registered under a name? Contact information like: name(amundbot, tcpip, [cavenan. idi. ntnu. no, 80]). name(amundbot, smtp, [amundbot@jfipa. org) name(amundbot, http, [www. jfipa. org: 80/])

Facilitators - I Agents performing various (useful) communication services 1. 2. 3. 4. 5. Maintain registry of service names Forward messages to named services Route messages based on content Provide ”matchmaking” Provide mediation and translation services

Routers • • • Content-independent message routers Each KQML-agent is associated with its own separate router process Router handles all outgoing/incoming ACL messages Outgoing messages can specify a particular agent address (to agent or router) Message can specify a description of context Delivery of messages is not guaranteed

Other ACLs • • Telescript – supports mobile computing FIPA ACL – competing/extending KQML • FIPA vs KQML – – – Both are based on speech act Different set of performatives FIPA has a more formal basis FIPA can describe interaction protocols FIPA is probably becoming the standard ACL

FIPA’s Agent Communication Language Specifications • More recently, the Foundation for Intelligent Physical Agents (FIPA) started work on a program of agent standards — the centerpiece is an ACL • Basic structure is quite similar to KQML: – performative 20 performative in FIPA – housekeeping e. g. , sender, etc. – content the actual content of the message

FIPA Example (inform : sender : receiver : content : language : ontology ) agent 1 agent 5 (price good 200 150) sl hpl-auction

FIPA

“Inform” and “Request” • “Inform” and “Request” are the two basic performatives in FIPA. All others are macro definitions, defined in terms of these. • The meaning of inform and request is defined in two parts: – pre-condition what must be true in order for the speech act to succeed – “rational effect” what the sender of the message hopes to bring about

“Inform” • For the “inform” performative… The content is a statement. Pre-condition is that sender: – holds that the content is true – intends that the recipient believe the content – does not already believe that the recipient is aware of whether content is true or not

“Request” • For the “request” performative… The content is an action. Pre-condition is that sender: – intends action content to be performed – believes recipient is capable of performing this action – does not believe that receiver already intends to perform action

What is FIPA? • • The Foundation for Intelligent Physical Agents (FIPA) is a non-profit association. FIPA’s purpose is to promote the success of emerging agent-based applications, services and equipment. FIPA’s goal is pursued by making available in a timely manner, internationally agreed specifications that maximise interoperability across agent-based applications, services and equipment. http: //www. fipa. org/

Who is FIPA? • • FIPA operates through the open international collaboration of member organisations, which are companies and universities active in the agent field. Companies: Alcatel, Boeing, British Telecom, Deutsche Telekom, France Telecom, Fujitsu, Hitatchi, HP, IBM, Fujitsu, Hewlett Packard, IBM, Intel, Lucent, NEC, NHK, NTT, Nortel, Siemens, SUN, Telia, Toshiba, etc. Universities and Research Institutes: GMD, EPFL, Imperial, IRST, etc. Government Agencies: DARPA

FIPA Encodings and package Fipa supports three main types of syntax encoding: 1. Extensible Markup Language – XML 2. Proprietary Binary format 3. Lisp-like format • Separates between Envelopes and Messages

Example - XML-encoded FIPA ACL 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. receiver@foo. com http: //foo. com/acc sender@bar. com http: //bar. com/acc fipa. acl. rep. xml. std 20000508 T 042651481 no encryption

Binary encoded FIPA XML 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 0 xfe 0 x 00 0 x 97 0 x 12 0 x 20 0 x 31 0 x 11 0 x 06 0 x 19 0 x 15 0 x 37 0 x 62 0 x 59 0 x 20 0 x 02 0 x 03 0 x 02 ‘r’ ‘e’ ‘c’ ‘e’ ‘i’ ‘v’ ‘e’ ‘r’ ‘@’ ‘f’ ‘o’ ‘. ’ ‘c’ ‘o’ ‘m’ 0 x 00 0 x 02 ‘h’ ‘t’ ‘p’ ‘: ’ ‘/’ ‘f’ ‘o’ ‘. ’ ‘c’ ‘o’ ‘m’ ‘/’ ‘a’ ‘c’ 0 x 00 0 x 01 0 x 02 ‘s’ ‘e’ ‘n’ ‘d’ ‘e’ ‘r’ ‘@’ ‘b’ ‘a’ ‘r’ ‘. ’ ‘c’ ‘o’ ‘m’ 0 x 00 0 x 02 ‘h’ ‘t’ ‘p’ ‘: ’ ‘/’ ‘b’ ‘a’ ‘r’ ‘. ’ ‘c’ ‘o’ ‘m’ ‘/’ ‘a’ ‘c’ 0 x 00 0 x 01 0 x 08 ‘n’ ‘o’ ‘ ’ ‘e’ ‘n’ ‘c’ ‘r’ ‘y’ ‘p’ ‘t’ ‘i’ ‘o’ ‘n’ 0 x 00 0 x 0 a ‘h’ ‘t’ ‘p’ ‘: ’ ‘/’ ‘b’ ‘a’ ‘r’ ‘. ’ ‘c’ ‘o’ ‘m’ ‘/’ ‘a’ ‘c’ 0 x 00 0 x 20 0 x 31 0 x 11 0 x 06 0 x 19 0 x 15 0 x 37 0 x 62 0 x 59 0 x 20 0 x 03 ‘ 1’ ‘ 2’ ‘ 3’ ‘ 4’ ‘ 5’ ‘ 6’ ‘ 7’ ‘ 8’ ‘ 9’ 0 x 00 0 x 01

Shortcomings of current ACLs • • • Intentional level description: which mental attitudes, what definitions? Problems with mental attitudes: from theory to practice Can all desirable communication primitives be modeled after speech acts? Should they? Flexible description of agents’ capabilities and advertising of such capabilities. How can we test an agent’s compliance with the ACL? Ease of extending an ACL

Conclusions of Current ACLs • Agent Communication Languages have a common basis – speech act • Syntax is well specified, but current research is on describing semantics

Motivation for KIF (Knowledge Interchange Format) http: //logic. stanford. edu/kif/dpans. html • • Creating language for development of intelligent applications Creating language for common interchange format Note: • KIF is not intended for interaction with humans • KIF is not intended to be internal representation for knowledge within computer programs

KIF Features 1. 2. 3. 4. Prefix version of 1 st order predicate calculus (logic) Declarative semantics Logically comprehensive Provides representation of knowledge about representation of knowledge Additional features: • Translatability • Readability • Usability

KIF General Overview Variables: • ? singlevar, @sequence Operators: Term Operators: listof, if, . . Sentence Operators: not, and, /=, . . . Rule Operators: =>>, . . Definition Operators: defobject, deffunction Constants: object, function, relational, logical Expressions: Word or a finite sequence of words (i. e. Sentences)

Agent Vocabularies • Agents should use words consistently Open-ended Dictionary • Each word has: – – • English description for understanding by humans KIF (or alternative) for understanding by computers Dictionary would contain multiple ontologies for many areas

Ontology Inference Layer – OIL http: //www. ontoknowledge. org/oil/ • • OIL is used to specify and exchange ontologies Three roots of OIL: 1. 2. Frame-based Systems 3. • Description Logics Web-standards: XML and RDF Small, not too expressive (as possibly the case with Ontolingua)

OIL Example ontology-container: title: ”african animals” subject: ”animal, food, vegetarians” description: ”example ontology describing african animals” Language ”en-uk” Source http: //www. url. com/ ontology-definitions: slot-def: eats inverse: is-eaten-by class-def: animal class-def: plant

Terminology of Agent Communication Speech Act – Formal subset of natural language representing actions ACL – Agent Communication Language FIPA - Foundation for Intelligent Physical Agents KQML – Knowledge Query and Manipulation Language Ontology – ”World Model”, formal description of agent domain Encoding – syntactic representation of ACL messages ACC – Agent Communication Channel (FIPA) KSE – Knowledge Sharing Effort KIF – Knowledge Interchange Format Router – entity that sends incoming messages in correct ”direction” Facilitator – An agent that includes a Router

Semantics on the Web - terminology Semantic Web RDF – Resource Decription Framework OIL – Open Inference Layer XML/XML Schema Ontolingua OKBC – Open Knowledge Base Connectivity DAML – DARPA Agent Markup Language DAML-S – Service description language based on DAML UDDI – Universal Description, Discovery and Integration WSDL – Web Services Description Language SHOE – Simple HTML Ontology Extensions eb. XML – e-business XML

Exercise • Read the paper: kqml-acl. pdf Present your understanding of the paper in 10 -15 minutes in next lecture.