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AOSE Multi-Agent Interaction

AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

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Page 1: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

AOSEMulti-Agent Interaction

Page 2: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Agents and Interaction

• Interaction forms the basis of an agents collaborative problem solving capabilities.– Agents are designed to operate in tandem with one another.– This includes sharing and requesting knowledge, negotiating

services, coordinating activities, …

• Key to realisation of such activities is the implementation of an underlying communication mechanism.

• Two broad approaches to communication:– Shared space communication– Communication by message passing

Page 3: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Message Passing

• General Principle:– Messages sent directly receiver agent (1:1 communication).– Message transmission handled by a communication channel.– Message format based on an agreed communication language.– Interaction consists of several messages where the agents take

their turns as sender and receiver.– This is called a dialog or a protocol.

• This model of message-passing is more traditional:– Modern message-oriented middleware supports factures such

as: presence management, message persistence, security, multcast, publish/subscribe, …

Page 4: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Message Passing

• Advantages:– Well suited to internet scale applications.– Communication is directed to relevant agents (no information

overload).– More Robust: So long as the communication channel is

decentralised.

• Disadvantages:– Agent Discovery: new agents must register their existence.– Choosing an appropriate communication language.– Defining and enforcing protocols.

Page 5: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Foundations

• A core issue underlying the design of message-passing based communication is the format of the messages.– Our goal is to support agent interactions that exhibit the flexibility

that is inherent within human conversation.

• As with many agent concepts, we look to philosophy in for inspiration…

• Speech Act Theory (Searle, 1969) is a pragmatic theory of language.– It attempts to account for how language is used by people every

day to achieve their goals and intentions.– It achieves this by adopting a view of speech as action.

Page 6: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Austin’s Theory

• The origin of speech act theories are usually traced to the work of the philosopher John Austin.

• Austin noticed that some utterances are like ”physical actions” that appear to change the state of the world. e.g.– Declaring war– ”I now pronounce you man and wife”

• Austin distinguished 3 different aspects of speech acts:– Locutionary act - act of making an utterance

• e.g. saying ”please make some tea” ’

– Illocutionary act – action performed in saying something• e.g. he requested me to make some tea

– Perlocution – effect of the act• e.g. he got me to make tea

Page 7: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Searle’s Theory

Searle built on Austins work and identified 5 types of illocutionary act (which he called speech acts):

Speech Act Type Description and Example

Representatives or Assertives

Informing

e.g. ”It is raining”.

Directives Speaker tries to make the hearer do something

e.g. ”Please close the window”

Commisives Commits the speaker to future action

e.g. ”I will close the window”

Expressives Speaker expresses a mental state

e.g. ”Excuse me”, ”congratulations”

Declaratives Effect some changes

e.g. ”I name this city Trondheim”

Page 8: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Speech Act Please close the door

The door is closed Is the door closed?

Performative request inform inquire

Content the door is closed the door is closed the door is closed

Searle’s Theory

He then determined that speech acts can be decomposed in to 2 core components:A performative verb

e.g. Request, inform

Propositional content

e.g. ”the window is closed”

Page 9: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Agent Communication Languages

• An Agent Communication Language combines:– a data format for representing speech acts.– a (partial) model of the state of the speaker and hearer.– a formally specified set of speech act types (based on the above

model).

• In theory:– speech act = performative verb + propositional content.

• In practice:– Contextual information, such as: who performed the speech act, and to

whom it was directed.

• Minimal Practical Form:– request ( rem, bob ) “closed(door)”

Page 10: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Agent Communication Languages

• Human communication employs other contextual information:– The language spoken (format), social rules governing the conversation

(protocol), the topic context / work meanings (ontology), …

• Typically, this information must also be provided in an ACL (although it is not always implemented in real world systems).

• Other information provided includes:– Encoding / Payload sizes / Routing Information

– Conversation Management Tokens (reply with / in response to)

• The key value of ACL’s is that they define a clear syntax and semantics for agent communication.

Page 11: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

AOSE

FIPA Agent Interaction

Page 12: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Who 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 operates through the open international collaboration of member organisations:– companies, universities and government organisations.

• FIPAs Standards Cover:– Agent Communication (FIPA ACL / Interaction Protocols)– AO-Application Infrastructures (Agent Platform, Agent Management,

Message Transport Systems)– Agent UML

Page 13: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

FIPA ACL: Structure

• Performative (communicative act)– 20 performatives in FIPA ACL

• Housekeeping– e.g. Sender, Reply to, Reply-with, In-Reply-With

• Content– the actual content of the message

• Language– The language in which the content is written

• Ontology– The ontology in which the message needs to be interpreted.

Page 14: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

FIPA ACL: Message Structure

• Envelope:– Comprises of a collection of

parameters

– Contains at least the mandatory to and sender parameters

• Message Body– The fully specified message in

the chosen ACL syntax

– Can be encoded (e.g. The FIPA Bit Efficient Encoding Mechanism).

Transport-message: HTTP

Sender:Transport-type: FIPA-HTTPTransport-address: http://www.agentfactory.com:4444/Transport-properties: none

Receiver:Transport-type: FIPA-HTTPTransport-address: http://www.ibeca.org:4444/Transport-properties: none

Additional-attributes:none

Payload(ACL message)

Envelope

Page 15: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

FIPA Transport management

•a platform provides each agent with a channel;

•a transfer protocol is used to transfer messages between channels;

•the transport service delivers messages within a platform or between platforms;

•ACL is the payload of the transport service and protocol;

•the envelope contains transport information.

Page 16: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

FIPA ACL: Performative Semantics

Inform Request

Content statement action

Precondition •Holds that the content is

true.

•Intends that the recipient

believe the content

•Does not already believe

that the recipient is aware

whether content is true or

not

•Intends action content to be

performed

•Believes recipient is capable

of performing this action

•Does not believe that sender

already intends to perform

action

Page 17: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Performatives in FIPA

Page 18: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

FIPA Agent Interaction Protocols

• Ongoing conversations between agents fall into typical patterns. – In such cases, certain message sequences are expected, and at

any point in the conversation, other messages are expected to follow.

• These typical patterns of message exchange are called protocols.

(query-if :sender A:receiver B:content some-act:protocol fipa-query-protocol

)

Page 19: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

FIPA Agent Interaction Protocols

• Basic FIPA Interaction Protocols:– Request Protocol– Query Protocol– Propose Protocol– Request When Protocol– Subscribe Protocol– Recruiting Protocol– Brokering Protocol

• Other FIPA Protocols:– English and Dutch Auctions, (Iterated) Contract Net

Page 20: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Example: Query Protocol

• The protocol states that:– IF an agent asks another

agent if a proposition holds or not

– THEN the participant must:– reply by informing the

initiator of the answer,– refuse to answer,– fail to answer, or– fail to understand the

question.

Page 21: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Example: Request Protocol

• Initiator requests that some activity / action be performed

• Participant either agrees or refuses request

• Next participant performs the activity / action:

• The initiator is informed of the result / completion of the action or that the action has failed.

Page 22: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Example: Subscribe Protocol

• Initiator subscribes to the participant.

• Participant either agrees or refuses subscription

• Participant informs initiator of any information relating to the subscription or sends a failure message if necessary.

Page 23: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Example: Brokering Protocol

Page 24: AOSE Multi-Agent Interaction. Agents and Interaction Interaction forms the basis of an agents collaborative problem solving capabilities. –Agents are

Example: Recruit Protocol