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Agent Technology

Agent Technology. Communication in multi-agent system. Communication. Message Types Communication Levels Speech Acts Knowledge Query and Manipulation Language Knowledge Interchange Format Ontology ACL Summary. Introduction. Motivation for Agent Communication

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Agent Technology

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  1. Agent Technology Communication in multi-agent system

  2. Communication • Message Types • Communication Levels • Speech Acts • Knowledge Query and Manipulation Language • Knowledge Interchange Format • Ontology • ACL • Summary ©Gao Yang, Ai Lab NJU

  3. Introduction • Motivation for Agent Communication • Communication is required for cooperation between agents. • Societies can perform tasks no individual agent can. • Autonomy encourages disregard for other agents’ internal structure. • Communication agents need only know a “common knowledge”. • Supports heterogeneous agents. ©Gao Yang, Ai Lab NJU

  4. Introduction • Characterization • Interactions occur when agents exist and act in close proximity • shared environment • shared resources • Communication occurs when agents send messages to one another with a view to influencing beliefs and intentions. • Implementation details are irrelevant • via communication links • through shared memory • because of shared conventions • signalling vs “talking” • “body language” ©Gao Yang, Ai Lab NJU

  5. Introduction • Communication • The primary reason for communication among agents is to coordinate activities • Agents may coordinate without communication, provided they have models of others’ behaviour • Communication involves the dimensions of • who • what • when • how (resources and protocol) • why • To facilitate cooperation, agents often need to communicate their intentions, goals, results, and state ©Gao Yang, Ai Lab NJU

  6. Introduction • Coordination and cooperation • Coordination is a property of interaction among agents performing some activity in a shared state. The degree of coordination is the extent to which they • avoid extraneous activity • reduce resource contention • avoid livelock • avoid deadlock • maintain safety conditions • Cooperation is coordination among non-antagonistic agents • Typically, agents must • maintain models of other agents • develop model of future interactions ©Gao Yang, Ai Lab NJU

  7. Introduction • Communication versus computation • Communication is generally more expensive and less reliable • recomputing is often faster than requesting information over a communication channel • communication can lead to prolonged negotiation • chains of belief and goal updates caused by communication may not terminate • Communication is qualitatively superior • information cannot always be reconstructed locally • communication can be avoided only when the agents are set up to share all necessary knowledge. This is a very limiting assumption which cannot be practically achieved in most interesting cases ©Gao Yang, Ai Lab NJU

  8. Introduction • MAS communication protocols • A MAS protocol is specified by the following fields: • sender • recipient(s) • language in the protocol • actions to be taken by the participants at various stages • A MAS protocol is defined above the ISO/OSI transport layer • not about bit patterns • not about retransmissions or routing • A MAS protocol is defined at the knowledge level • involves high-level concepts, such as • commitments, beliefs, intentions • permissions, responsibilities, requests ©Gao Yang, Ai Lab NJU

  9. Message Types • Two basic message types • Assertions • In the simplest form, the information is communicated to the agent from an external source by means of an assertion. • Query • In order to assume a passive role in a dialog, an agent must additionally be able to answer questions, i.e., it must be able to • 1) accept a query from an external source and 2) send a reply to the source by making an assertion. ©Gao Yang, Ai Lab NJU

  10. Message Types • Two basic message types • Query • In order to assume an active role in a dialog, an agent must be able to issue queries and make assertions. ©Gao Yang, Ai Lab NJU

  11. Message Types • Interagent message types ©Gao Yang, Ai Lab NJU

  12. Communication Levels • Communication protocols’ levels • The lowest level of the protocol specifies the method of interaction; • The middle level specifies the format, or syntax, of the information being transferred; • The top level specifies the meaning, or semantics, of the information. • Binary and N-ary communication protocols • Sender and Receiver(s) • Language in the protocol • Encoding and decoding functions • Actions to be taken by the receiver(s) ©Gao Yang, Ai Lab NJU

  13. Communication Levels • Levels of agent communication Agent Communication Language FIPA-ACL, KQML, ... Content language XML, KIF, WML, HTML, ... Agent middleware Encoding schema Java serialized object, String, Bytecode Physical protocols HTTP, IIOP, TCP/IP, SMTP, Fax, Phone, WAP, ... ©Gao Yang, Ai Lab NJU

  14. Communication Levels • Classification of message classifications • Syntactic • distinguish messages based on grammatical forms in natural language • Semantic • distinguish messages based on a notion of intrinsic meaning • e.g., prohibitive is different from directive, despite their syntactic similarity • Use-based • distinguish messages based on their roles in specific classes of protocols • e.g., assertion is different from acknowledgment ©Gao Yang, Ai Lab NJU

  15. Communication Levels • How can an agent tell another agent something? • Send the information in a message (message passing) • Write the information in a location where the other agent is likely to look (shared memory, blackboard) • Show or demonstrate to the other agent (teaching) • Insert or program the information directly into the other agent (master-slave, controller-controller) ©Gao Yang, Ai Lab NJU

  16. Communication Levels • How can one agent obtain information or request a service from another agent? • Ask the other agent (message passing) • Read a location where the other agent is likely to write something (shared memory or blackborad) • Observe the other agent (learning) • Access the information directly from the other agent (“brain surgery”) ©Gao Yang, Ai Lab NJU

  17. Speech Acts • The model for communication among computational agents • Spoken human communication, speech act theory. • Speech act theory views human natural language as actions, such as requests, suggestions, commitments, and replies. • For example: • When a jury declares a defendant guilty, there is an action taken: the defendant’s social status is changed. ©Gao Yang, Ai Lab NJU

  18. Speech Acts • A speech act has three aspects: • Locution, the physical utterance by the speaker. • Illocution, the intended meaning of the utterance by the speaker. • Perlocution, the action that results from the locution. • For example: John say to Mary, “Pls close the window.” • This act consists of the physical sounds generated by John. • John’s intent for the message as a request or a command. • If all goes well, the window being shut. ©Gao Yang, Ai Lab NJU

  19. Speech Acts • But, the intent of the message is not always easily identified. • For example: “I’m cold” • Can be viewed as an assertion, a request for a sweater, or a demand for an increase in room temperature. • For communication among agents, we want to insure that there is no doubt about the type of message. ©Gao Yang, Ai Lab NJU

  20. Speech Acts • Performative • Speech act theory uses the term performative to identify the illocutionary force of this special class of utterance. • Example performative verbs include • Promise, report, convince, insist, tell, request, and demand etc. • The special of performative verbs • “Saying it makes it so”. • Not all verbs are performative, “I solve this problem”. ©Gao Yang, Ai Lab NJU

  21. Speech Acts • Performative • Example performative verbs can be broadly classified as • Assertives (statements of fact). • Directives (commands in a master-slave structure) • Commissives (commitments) • Declaratives (statements of fact) • Expressive (expressions of emotion) ©Gao Yang, Ai Lab NJU

  22. Speech Acts ©Gao Yang, Ai Lab NJU

  23. Speech Acts • In summary • Speech act theory helps define the type of message by using the concept of the illocutionary force, which constrains the semantics of the communication act itself. • But, the message contained within the protocol may be ambiguous • may have no simple response; • Or may require decomposition and the assistance of other agents. ©Gao Yang, Ai Lab NJU

  24. KQML • A foundamental decision for the interaction of agents • Separate the semantics of the communication protocol (which must be domain independent) from the semantics of the enclosed message (which may depend on the domain) • Protocol should be concise and have only a limited of primitive communication acts. ©Gao Yang, Ai Lab NJU

  25. KQML • KQML • Developed under a DARPA funded project, started around 1990 • Is a protocol for exchange information and knowledge. • Two specifications: • DARPA Knowledge Sharing Initiative 1993 • Yannis Labrou and Tim Finin 1997 ©Gao Yang, Ai Lab NJU

  26. KQML • KQML • The elegance of KQML • Is that all information for understanding the content of the message is include in the communication itself. • Each message represents a speech act, associated semantics, protocol and a list of attributes • The basic protocol is defined by the following structure. (KQML-performative :sender <word> :receiver <word> :language <word> :ontology <word> :content <expression> ……) ©Gao Yang, Ai Lab NJU

  27. KQML • KQML • The syntax is Lisp-like, the arguments-identified by keywords preceded by a colon-may be given in any order. • KQML performatives • Describes the type of the message. • About 25 reserved performatives names. • Additional performatives can be added. • Special administrative and networking message type. ©Gao Yang, Ai Lab NJU

  28. KQML • The KQML-performatives are modeled on speech act performatives. • Thus, the semantics of KQML performatives is domain independent. • :content the message itself. • :language the language in which the message is expressed. • :ontology the vocabulary of the “words” in the message. ©Gao Yang, Ai Lab NJU

  29. KQML • KQML • The terms :content, :language, and :ontology delineate the semantics of the language. • Other arguments, including :sender, :receiver, :reply-with, and :in-reply-to, are parameters of the message passing. • KQML can be used in asynchronous communications. • Enough? • KIF: a formal syntax for representing knowledge. • Ontology: define the common concepts, attributes, and relationships for different subsets of world knowledge. ©Gao Yang, Ai Lab NJU

  30. KQML • Blocks-World example • In a Blocks-World ontology, the fact that block A is on top of block B could be communicated as follows: (tell :sender Agent1 :receiver Agent2 :language KIF :ontology Blocks-World :content (And (Block A) (Block B) (On A B)) ) ©Gao Yang, Ai Lab NJU

  31. KQML • For an asynchronous communication, if Agent1 cannot communicate directly with Agent2(but can communicate with Agent3), Agent1 might ask Agent3 to forward a message to Agent2: (forward :from Agent1 :to Agent2 :sender Agent1 :receiver Agent3 :language KQML :ontology kqml-ontology :content (tell :sender Agent1 :receiver Agent2 :language KIF :ontology Blocks-World :content (And (Block A) (Block B) (On A B)))) ©Gao Yang, Ai Lab NJU

  32. KQML • The KQML performatives may be organized into seven basic categories: • Basic query performatives (evaluate, ask-one, ask-all, …) • Multiresponse query performatives (stream-in, stream-all, …) • Response performatives (reply, sorry, …) • Generic information performatives (tell, achieve, cancel, untell, unachieve,…) • Generator performatives (standby, ready, rest, …) • Capability-definition performatives (advertise, subscribe, monitor, …) • Networking performatives (register, unregister, forward, broadcast, …) ©Gao Yang, Ai Lab NJU

  33. KQML (advertise :sender Agent2 :receiver Agent1 :language KQML :ontology kqml-ontology :content (ask-all :sender Agent1 :receiver Agent2 :in-reply-to id1 :language Prolog :ontology Blocks-World :content “on(X,Y)”)) ©Gao Yang, Ai Lab NJU

  34. KQML (ask-all :sender Agent1 :receiver Agent2 :in-reply-to id1 :language Prolog :ontology Blocks-World :content “on(X,Y)”)) (tell :sender Agent2 :receiver Agent1 :in-reply-to id2 :language Prolog :ontology Blocks-World :content “[on(a,b), on(c,d)]”) ©Gao Yang, Ai Lab NJU

  35. KQML • The communication infrastructure • Is not part of the KQML specification • Implemented system use custom-made utility programs called routers or facilators to perform this function. ©Gao Yang, Ai Lab NJU

  36. KQML • 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/]) ©Gao Yang, Ai Lab NJU

  37. KQML • Facilitators – 1 • Maintain registry of service names • Forward messages to named services • Route messages based on content • Provide ”matchmaking” • Provide mediation and translation services ©Gao Yang, Ai Lab NJU

  38. KQML • Facilitators – I (F is not involved) ©Gao Yang, Ai Lab NJU

  39. tell(X) ask(X) F tell(X) A B KQML • F just forwards ©Gao Yang, Ai Lab NJU

  40. KQML • F is the middle-man ©Gao Yang, Ai Lab NJU

  41. KQML • F sets up connection ©Gao Yang, Ai Lab NJU

  42. KQML • Service discovery ©Gao Yang, Ai Lab NJU

  43. KQML • 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 ©Gao Yang, Ai Lab NJU

  44. Communication:Mechanics of communication Message:Logic of communication Content of communication KQML • Summary • KQML aims to add value at the semantic level of communication • KQML is based on speech act theory (performatives) • KQML provides a meta language describing an envelope, and allowing arbitrary content languages • KQML is meant to be used for: • Agent-to-application communication • Agent-to-agent communication • KQML is layered: ©Gao Yang, Ai Lab NJU

  45. KQML • KQML communication assumptions • Agents are connected by unidirectional links carrying discrete messages • Links have nonzero transport delay • Agent knows link of received message • Agent controls link for sending • Messages to a single destination arrive in the order they were sent • Message delivery is reliable, i.e., no messages are lost ©Gao Yang, Ai Lab NJU

  46. KQML • KQML semantics • Each agent manages a virtual knowledge base (VKB) • Statements in a VKB can be classified into • beliefs • goals • Beliefs encode information an agent has about itself and its environment • Goals encode states of an agent’s environment that it will act to achieve • Agents use KQML to communicate about the contents of their own and others’ VKB ©Gao Yang, Ai Lab NJU

  47. KQML • Critique of KQML • Notion of semantics: NOT semantics of the language, but an operational semantics of the agents in applying the pragmatics of the language • So far, KQML work has been merely driven by academia • No industry standard implementation • No consideration of industry standards (e.g., CORBA, XML) • Messaging paradigm behind KQML leads to high learning curve for developers • KQML has concentrated too much on syntax so far, where the contribution could have been in enhancing semantics • So far, KQML has had only little impact on and virtually no use in industrial software engineering and system development ©Gao Yang, Ai Lab NJU

  48. Knowledge Interchange Format • Motivation for KIF • 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 is specifically designed to serve as an ”interlingua”, or mediator in the translation of other language. ©Gao Yang, Ai Lab NJU

  49. Knowledge Interchange Format • KIF features • Prefix version of 1st order predicate calculus (logic) • Declarative semantics • Logically comprehensive • Provides representation of knowledge about representation of knowledge • Additional features: • Translatability • Readability • Usability ©Gao Yang, Ai Lab NJU

  50. Knowledge Interchange Format • 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) ©Gao Yang, Ai Lab NJU

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