Multi-Agent Systems Lecture 3 University “Politehnica” of Bucarest 2004-2005 Adina Magda Florea

Slides:



Advertisements
Similar presentations
DISTRIBUTED COMPUTING PARADIGMS
Advertisements

1DAML PI meeting, October DAML and Agents DAML and Agents Breakout Session DAML PI Meeting 17 October 2002 Tim Finin.
ARCHITECTURES FOR ARTIFICIAL INTELLIGENCE SYSTEMS
8-1 LECTURE 8: Agent Communication An Introduction to MultiAgent Systems
FIPA Interaction Protocol. Request Interaction Protocol Summary –Request Interaction Protocol allows one agent to request another to perform some action.
Web Service Ahmed Gamal Ahmed Nile University Bioinformatics Group
Chapter 16: Multiagent Systems Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005.
Chapter 18: Communication Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005.
OASIS Reference Model for Service Oriented Architecture 1.0
Specifying Agent Interaction Protocols with AUML and OCL COSC 6341 Project Presentation Alexei Lapouchnian November 29, 2000.
Software Agent -communication-. Outline Overview Speech act theory Agent communication languages Summary 1/35.
Chapter 8 The nature of communication
INTERACTION AND COMMUNICATION. Coordination A property of interaction among a set of agents performing some activity in a shared state. The degree of.
Multi-Agent Systems Chapter 2 Adapted (with permission) from Adina Magda Florea
Multiagent Systems and Societies of Agents
Agent Communication Languages CSE5610- Intelligent Software Systems Agent Communication Languages.
Agent Communication Language. Agent Coordination Agents communicate in order to achieve better the goals of themselves or of the society Coordination.
From SHIQ and RDF to OWL: The Making of a Web Ontology Language
01 -1 Lecture 01 Intelligent Agents TopicsTopics –Definition –Agent Model –Agent Technology –Agent Architecture.
Systems Architecture, Fourth Edition1 Internet and Distributed Application Services Chapter 13.
KQML as an Agent Communication Language Tim Finin, Yannis Labrou, James Mayfield.
Web Service Architecture Part I- Overview and Models (based on W3C Working Group Note Frank.
Agents Communication Languages (ACL) Dumitru Roman Digital Enterprise Research Institute
2015/8/91 FIPA Communicative Acts (CA). 2015/8/92 Introduction to FIPA FIPA is an IEEE Computer Society standards organization that promotes agent-based.
Multi-Agent Systems University “Politehnica” of Bucarest Spring 2011 Adina Magda Florea curs.cs.pub.ro.
Computer Science 30/08/20151 Agent Communication BDI Communication CPSC /CPSC Rob Kremer Department of Computer Science University of Calgary.
Topic 5: Communication and Negotiation Protocols
Agent Communication The nature of communication Indirect communication
The Semantic Web Service Shuying Wang Outline Semantic Web vision Core technologies XML, RDF, Ontology, Agent… Web services DAML-S.
SIF8072 Distributed Artificial Intelligence and Intelligent Agents 13 February 2003 Lecture 5: Agent Communication Lecturer:
EEL 5937 Agent communication EEL 5937 Multi Agent Systems Lecture 10, Feb. 6, 2003 Lotzi Bölöni.
Chapter 18: Communication Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005.
DISTRIBUTED COMPUTING PARADIGMS. Paradigm? A MODEL 2for notes
Agent Communications Necessity Communication languages Communication architectures.
ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.
Multi-Agent Systems Lecture 3 University “Politehnica” of Bucarest Adina Magda Florea
An Ontological Framework for Web Service Processes By Claus Pahl and Ronan Barrett.
©Ferenc Vajda 1 Semantic Grid Ferenc Vajda Computer and Automation Research Institute Hungarian Academy of Sciences.
Design of Multi-Agent Systems Teacher Bart Verheij Student assistants Albert Hankel Elske van der Vaart Web site
AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are.
Introduction to Semantic Web Service Architecture ► The vision of the Semantic Web ► Ontologies as the basic building block ► Semantic Web Service Architecture.
Chapter 5: Distributed objects and remote invocation Introduction Remote procedure call Events and notifications.
EEL 5937 Agent communication EEL 5937 Multi Agent Systems Lotzi Bölöni.
Agent Overview. Topics Agent and its characteristics Architectures Agent Management.
1 Chapter 38 RPC and Middleware. 2 Middleware  Tools to help programmers  Makes client-server programming  Easier  Faster  Makes resulting software.
Intelligent Agents: Technology and Applications Agent Communications IST 597B Spring 2003 John Yen.
Agent Communication Languages Speech act theory Speech act theory Semantics of languages Semantics of languages KQML KQML FIPA ACL FIPA ACL Comparison.
Computer Science 24/02/20161 Agent Communication FIPA Performatives CPSC /CPSC Rob Kremer Department of Computer Science University of Calgary.
EEL 5937 Content languages EEL 5937 Multi Agent Systems Lecture 10, Feb. 6, 2003 Lotzi Bölöni.
Understanding Naturally Conveyed Explanations of Device Behavior Michael Oltmans and Randall Davis MIT Artificial Intelligence Lab.
MTA SZTAKI Department of Distributed Systems Hogyan mixeljünk össze webszolgáltatásokat, ontológiákat és ágenseket? Micsik András.
Software Architecture for Multimodal Interactive Systems : Voice-enabled Graphical Notebook.
다중 에이전트의 의사소통 모델에 관한 연구 - KQML 언어의 의미론을 중심으로 - 인지과학 협동과정 김 경수.
Agent Communication Michael Floyd SYSC 5103 – Software Agents November 13, 2008.
Topic 4: Distributed Objects Dr. Ayman Srour Faculty of Applied Engineering and Urban Planning University of Palestine.
OKBC (Open Knowledge Base Connectivity) An API For Knowledge Servers
Service-Oriented Computing: Semantics, Processes, Agents
LECTURE 9: Agent Communication
Service-Oriented Computing: Semantics, Processes, Agents
Web Service Modeling Ontology (WSMO)
Agent communication Lecture outline
Copyright © 2011 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 2 Database System Concepts and Architecture.
Service-Oriented Computing: Semantics, Processes, Agents
Chapter 2 Database Environment.
Service-Oriented Computing: Semantics, Processes, Agents
Service-Oriented Computing: Semantics, Processes, Agents
AGENT FRAMEWORK By- Arpan Biswas Rahul Gupta.
Semantic Resolution in a Simple E-Commerce Application
Presentation transcript:

Multi-Agent Systems Lecture 3 University “Politehnica” of Bucarest Adina Magda Florea

Agent communication Lecture outline  The nature of communication  Indirect communication  Direct communication  Agent Communication Languages Content languagesContent languages OntologiesOntologies Theory of speech actsTheory of speech acts KQMLKQML FIPA and FIPA-ACLFIPA and FIPA-ACL  Interaction protocols

1. The nature of communication 1.1 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 1.2 Component steps of communication SpeakerHearer  Intention  Perception  Generation  Analysis  Synthesis  Disambiguation  Incorporation 3 Syntax Semantics Pragmatics

Communication model

1.3 Artificial Communication   low-level language vs high-level languages   direct communication vs. indirect communication Computer communication   shared memory message passing Agent communication/ MAS communication   low-level communication: simple signals, traces, low-level languages   high-level communication - cognitive agents, mostly seen as intentional systems   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 5

Communication protocols Communication protocols = enables agents to exchange and understand messages Interaction protocols Interaction protocols = enable agents to have conversations, i.e., structured exchanges of messages Aim Aim  Communication enables agents to:   coordinate their actions and behavior, a property of a MAS performing some activity in a shared environment   attempt to change state of the other agents   attempt to make the other agents perform some actions 6

2. Indirect communication 2.1 Signal propagation 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 decreases   At a point x, the signal may have one of the following intensities V(x)=V(x 0 )/dist(x,x 0 ) or V(x)=V(x 0 )/dist(x,x 0 ) 2 7  x0x0  S S - stimulus  Agent A (stimulus triggers behavior P) Agent B (stimulus triggers behavior P) 2.2 Trails 2.2 Trails - L. Steels, 1995  agents drop "radioactive crumbs" making trails  an agent following a trail makes the trail faint until it disappears Reactive agents

2.3Blackboard systems 2.3 Blackboard 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 to receive an access authorization to the blackboard   Blackboard = a distributed knowledge computation paradigm   Agents = Knowledge sources (KS) 8 Cognitive agents KS KSAR Control Blackboard

3. Direct communication Sending messages   method invocation – Actors   exchange of partial plans – coordination of cooperative agents ACL = Agent Communication Languages   Need to communicate knowledge  knowledge representation   Need to understand the message in a context  ontologies   Communication is seen as an action - communicative acts 9

Concepts (distinguish ACLs from RPC, RMI or CORBA, ORB):   An ACL message describes a desired state in a declarative language, rather than a procedure or method invocation   ACLs handle propositions, rules, and actions instead of objects with no associated semantics - KR   ACLs are mainly based on BDI theories: BDI agents attempt to communicate their BDI states or attempt to alter interlocutor's BDI state – Cognitive Agents   ACLs are based on Speech Act Theory – Communicative Acts   ACLs refer to shared Ontologies   Agent behavior and strategy drivecommunication and lead to conversations - Protocols Agent Communication Languages

11 Origins of ACLs Knowledge Sharing Effort - DARPA, 1990  External Interface Group - interaction between KBS - KQML  Interlingua - common language of KB - KIF  Shared, Reusable Knowledge Bases - Ontolingua ACL Content language Ontology   Communication primitives and protocols   Content languages KIF Prolog Clips SQL FIPA-SL, FIPA-KIF   Ontologies   DAML   OWL DARPA Agent Markup Language (August 2000). The goal of the DAML effort is to develop a language and tools to facilitate the concept of the Semantic Web.

Content languages for ACL (Knowledge representation)  Description Logics (DL) - a formalism for expressing concepts and their interrelationships. In DL, concepts are organized into IS-A hierarchies. Concepts are specifications such that given an individual (object instance) a DL system can recognize the individual and determine which concepts it belongs to. DL systems also perform subsumption checking.  Knowledge Interchange Format (KIF) - is based on first order predicate logic and has a LISP-like prefix syntax. KIF is capable of expressing facts and complex relationships (rules). KIF provides constructs for describing procedures, i.e. programs to (possibly) be executed by an agent.

13 Knowledge Interchange Format (KIF)  Facts (salary john 72000) (salary michael 36000) (salary sam 42000)  Asserted relation (> (* (width chip1) (length chip1)) (* (width chip2) (length chip2)))  Rule (=> (and (real-number ?x) (even-number ?n)) (> (expt ?x ?n) 0))  Procedure (progn (fresh-line t) (print "Hello!") (fresh-line t))

Ontologies Ontology = a specification of objects, concepts, and reationships in a particular domain; it comprises a vocabulary, a domain theory and a conceptual schemata to describe organization and interpretation  An ontology is more than a taxonomy of classes, it must also describe relationships  Lexicalized ontologies (WordNet, EuroWordNet, BalkanNet, FrameNet, MikroKosmos).  Ontologies for knowledge representation  Implicit ontologies (class libraries of OOP) Person PupilStudEmpl Sun_EIBM_E Person Empl Woman Stud Man JoeAlice JoeAlice

15  x (Block x)  (PhysicalObject x) Instead of saying (Block A) (InstanceOf A Block) Define the hierarchy (Class Block) (Class PhysicalObjects) (SubclassOf Block PhysicalObjects)  x,y,z (InstanceOf x y)  (SubclassOf y z)  (InstanceOf x z) Ontology editors = frame-based KR systems that allow the user to define an ontology and its components: classes, instances, relationships, and functions

OWL - Web Ontology Language   W3C   OWL - designed for use by applications that need to process the content of information instead of just presenting information to humans.   OWL facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics.   OWL has three increasingly-expressive sublanguages:   OWL Lite supports a classification hierarchy and simple constraints.   OWL DL supports maximum expressiveness while retaining computational completeness (all conclusions are guaranteed to be computed) and decidability (all computations will finish in finite time).   OWL Full supports maximum expressiveness and the syntactic freedom of RDF with no computational guarantees.

OWL - Web Ontology Language Ontology header An example OWL ontology Wine Ontology … Simple Named Classes Class, rdfs:subClassOf

3.4 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 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" locutionillocutioncontent prelocution: door closed (hopefully!) Illocutionary aspect - several categories o oAssertives, which inform: the door is shut o oDirectives, which request: shut the door, can pelicans fly? o oCommissives, which promise something: I will shut the door o oPermissive, which gives permission for an act: you may shut the door o oProhibitives, which ban some act: do not shut the door o oDeclaratives, which causes events: I name you king of Ruritania o oExpressives, which express emotions and evaluations: I am happy 18

3.5 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 19 Content Communication Message Describes low level communication parameters: - identity of sender and receiver - an unique id associated with the communication Core of KQML - identity of the network protocol with which to deliver the message - speech act or performative Optional - content language - ontology

Syntax SyntaxS-expressions used in LISP KQML performatives are classified:   Queries - These performatives are used to send questions for evaluation somewhere.   Generative - Used for controlling and initiating the exchange of messages.   Response - Used by a agent in order reply to queries.   Informational - Informational performatives are used to transfer information.   Capability definition - Allows an agent to learn about the capabilities of other agents and to announce its own to the agent community.   Networking - Networking performatives make it possible to pass directives to underlying communication layers.Example (ask-one :sender joe :receiver ibm-stock :reply-with ibm-stock :language PROLOG :ontology NYSE-TICKS :content (price ibm ?price) ) 20 (tell:sender willie :receiver joe :reply-with block1 :language KIF :ontology BlockWorld :content (AND (Block A)(Block B) (On A B)) )

21 1. Query performatives: ask-one, ask-all, ask-if, stream-all,... (stream-all:sender willie :receiver ibm-stock :content (price ?VL ?price ) ) ask-one(P) tell(P) tell(P1) stream-all(P) tell(P2) eos tell(P1,P2,...) ask-all(P) B B B A A A

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

23 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 tell(P) ask(P) subscribe(ask(P)) tell(P) advertise(ask(P)) tell(P) recruit(ask(P)) reply(A) recommend(ask(P))advertise(ask(P)) tell(P) ask(P) reply(B) A A A A B B B B point-to-point

24 Semantics of KQML (Labrou & Finin)  Use preconditions and postconditions that govern the use of a performative + the final state for the successful performance of the performative  Uses propositional attitudes: belief, knowledge, desire, intentions Preconditions: the necessary states for an agent to send a performative and for the receiver to accept it and successfully process it; if the precondition does 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 Propositional attitudes Bel(A,P)Know(A,S)Want(A,S)Int(A,S) Instances of action Proc(A,M)SendMsg(A,B,M)

25 tell(A,B,X) 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, Bel(A,X)))) Pre(B): Int(B, Know(B, Bel(A,X))) or  Bel(A,X) Post(A): Know(A, Know(B, Bel(A,X))) no unsolicited information Post(B): Know(B, Bel(A,X)) Completion: Know(B, Bel(A,X))advertise(A,B,M) A states to B that A can and will process the message M from B, if it receives one Int(A, Proc(A,M))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)))

26 KQML Software architecture KQML – implemented in different languages  Design – a router, a facilitator, a library of interface routines (KRIL)  Eack KML agent is associated with its separate router process; all routers are identical Agent KRILRouter Network KQML objects function calls Network connections KQML strings

27 KRIL An API – KQML Router Interface Library  While the router is a separate process, with no undestanding of the content field of a KQML message, the KRIL API is embedded in the application and has access to the application tools for analyzing the content.  Variuos KRILs  Tightly embedded or lightly embedded  Simple KRIL - send-kqml-message – accepts a message - declare-message-handler – which function to invoke when a message arrives - different types of declarations which allow to register the application with local facilitators and contact remote agents  KRIL: Common Lisp, C, Prolog, SQL, etc.

FIPA and FIPA - ACL Foundation for Intelligent Physical Agents, 1996 o Goal of FIPA = make available specifications that maximize interoperability across agent-based systems o FIPA Committees: ACL, agent specification, agent-software interaction  As KQML, FIPA ACL is based on speech act theory; it sees messages as communication acts (CA); syntax similar to KQML  Differs in: the names of CAs, set of CAs, and semantics FIPA communicative acts Informatives - query_if, subscribe, inform, inform_if, confirm, disconfirm, not_understood Task distribution - request, request_whenever, cancel, agree, refuse, failure Negotiation - cfp, propose, accept_proposal, reject_proposal

29 FIPA's specifications are grouped into 5 categories:  1. Applications  2. Abstract Architecture  3. Agent Communication  4. Agent Management  5. Agent Message Transport 3. Agent Communication: FIPA ACL Message Structure  Communicative Acts: FIPA Communicative Acts Library  Content Languages:  FIPA Content Languages  FIPA SL Content Language  FIPA CCL Content Language  FIPA KIF Content Language  FIPA RDF Content Language  Interaction Protocols

30  FIPA-SL (Semantic Language) (inform:sender Agent1 :receiver Agent2 :content (price good2 150) :in-reply-to round-1 : reply-with bid03 : language S1 :ontology hp-auction :reply-by 10 :protocol offer :conversation-id conv-1 )

31  FIPA-SL (request :sender (agent-identifier :name i) :receiver (set (agent-identifer :name j) :content ((action (agent-identifier :name j) (deliver box7 (loc 10 15)))) :protocol fipa-request :language fipa-sl :reply-with order56 ) (agree :sender (agent-identifier :name j) :receiver (set (agent-identifer :name i) :content ((action (agent-identifier :name j) (deliver box7 (loc 10 15))) (priority order56 low)) :protocol fipa-request :language fipa-sl :in-reply-to order56 )

32 FIPA - Semantics SL (Semantic Language) - a quantified, multi-modal logic, with modal operators Allows to represent:  beliefs  uncertain beliefs  desires  intentions B  - beliefD  - desireU  - uncertain belief PG  - intention Bif  - express whether an agent has a definite opinion one way or another about the truth or falsity of  Uif  - the agent is uncertain about 

33 FIPA - Semantics The semantics of a CA 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 to occur 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 Pre: B A    B A (Bif B   Uif B  ) Post: B B 

34 Using ACLs in MAS 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

4. Interaction protocols Interaction protocols Interaction protocols = enable agents to have conversations, i.e., structured exchanges of messages   Finite automata   Conversations in KQML   Petri nets   FIPA IP standards: FIPA-query, FIPA-request, FIPA-contract-net,...

4.1 Finite state automata 36 A:B<<ask(do P) B:A<<accept(do P) B:A<<refuse(do P) B:A<<result(do P)B:A<<fail(do P) propose S (P) accept R (P) reject R (P) counter R (P) counter S (P) accept S (P) reject S (P) Winograd, Flores, 1986 COOL, Barbuceanu,95

Conversations in KQML 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 A wants to do P, A cannot do P Request do(P) Refuse do(P) Accept/request do(P) Fail to do(P) Notification of end(P) DBAR1AR2 FA2 FA1 BR FB Failure Satisfaction Impossible to do(P) B does not want to do(P) B is willing to do(P) Completed(P) 4.3 Petri nets 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. Tokens are moved from place to place, following firing rules. A transition T is enabled if all the input places P of T posses a token (several other rules may be defined). A marking is a distribution of tokens over places. Colored Petri-nets Ferber, Success

FIPA Interaction Protocols FIPA Interaction Protocol Library  FIPA Request Interaction Protocol  FIPA Query Interaction Protocol  FIPA Request When Interaction Protocol  FIPA Contract Net Interaction Protocol  FIPA Iterated Contract Net Interaction Protocol  FIPA English Auction Interaction Protocol  FIPA Dutch Auction Interaction Protocol  FIPA Brokering Interaction Protocol  FIPA Recruiting Interaction Protocol  FIPA Subscribe Interaction Protocol  FIPA Propose Interaction Protocol

40 References  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  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  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,  M. Singh. Agent communication languages: Rethinking the principles. IEEE Computer, Dec. 1998, p  Y. Labrou, T. Finnin, Y. Peng. Agent communication languages: The current Landscape. IEEE Computer, March/April 1999, p  FIPA97. "Agent Communication Language" Specification FIPA, 11/28/97

41 Web References DARPA KSEhttp://www-ksl.stanford.edu/knowledge-sharing/ KQMLhttp:// KIFhttp://logic.stanford.edu/kif/ Ontolinguahttp://www-ksl-svc.stanford.edu:5915/&service=frame-editorhttp://www-ksl-svc.stanford.edu:5915/&service=frame-editor FIPAhttp:// DAMLhttp:// OWLhttp:// References for Ontologies References for Ontologies (due to prof. Stefan Trausan)  Constandache, G.G., Ştefan Trăuşan-Matu, Ontologia şi hermeneutica calculatoarelor, Ed. Tehnică, 2001  Gruber, T., What is an Ontology,  J. Sowa, Ontologia şi reprezentarea cunoştinţelor, în (Constandache şi Trăuşan-Matu, 2001)  