RuleML Query Answering with RuleML Query Answering with Personal OO jDREW Agents in Personal OO jDREW Agents in
Rule Responder Rule Responder Benjamin CraigBenjamin Craig
Harold BoleyHarold Boley Fredericton, NBFredericton, NB
National Research Council - IITNational Research Council - IIT
May 15, 2008May 15, 2008
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OutlineOutline Rule Responder OverviewRule Responder Overview AgentsAgents
Personal / Organizational / ExternalPersonal / Organizational / External Rule Engines Rule Engines (for Realizing Agents)(for Realizing Agents)
ProvaProva OO jDREWOO jDREW
Communication Middleware Communication Middleware (for Connecting (for Connecting Agents)Agents) Mule ESBMule ESB Reaction RuleML MessagesReaction RuleML Messages
Symposium Planner Use CaseSymposium Planner Use Case Online DemoOnline Demo
ConclusionConclusion
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Overview of Rule Responder Overview of Rule Responder (I)(I)
Rule Responder is an experimentalRule Responder is an experimentalmulti-agent system for collaborative multi-agent system for collaborative teams and virtual communities on the teams and virtual communities on the WebWeb
Supports rule-based collaboration Supports rule-based collaboration between the distributed members of between the distributed members of such a virtual organizationsuch a virtual organization
Members of the virtual organization are Members of the virtual organization are assisted by semi-automated rule-based assisted by semi-automated rule-based agents, which use rules to describe the agents, which use rules to describe the behavioral and decision logicbehavioral and decision logic
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Overview of Rule Responder Overview of Rule Responder (II)(II)
Uses languages and engines of the Uses languages and engines of the RuleML family for rule serialization, RuleML family for rule serialization, based on logic and XML: based on logic and XML: Hornlog RuleML: ReasoningHornlog RuleML: Reasoning Reaction RuleML: Interaction Reaction RuleML: Interaction
Implemented on top of a Mule-basedImplemented on top of a Mule-basedService Oriented Architecture (SOA)Service Oriented Architecture (SOA)
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Personal AgentsPersonal Agents
A personal agent assists a single personA personal agent assists a single person
of an organization, (semi-autonomously) of an organization, (semi-autonomously)
acting on his/her behalfacting on his/her behalf It contains a FOAF*-like fact profile plus It contains a FOAF*-like fact profile plus
FOAF-extending rules to encode some of FOAF-extending rules to encode some of
the knowledge of its human ownerthe knowledge of its human owner
* The Friend of a Friend (FOAF) project: http://www.foaf-project.org
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Organizational AgentsOrganizational Agents
An organizational agent represents An organizational agent represents goals and strategies shared by each goals and strategies shared by each member of the organizationmember of the organization
It contains rule sets that describe the It contains rule sets that describe the policies, regulations, opportunities, policies, regulations, opportunities, etc. of its organization etc. of its organization
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External AgentsExternal Agents
External agents communicate with the External agents communicate with the public interface of organizational public interface of organizational agents, exchanging messages that agents, exchanging messages that transport queries, answers, or complete transport queries, answers, or complete rule sets rule sets
End users, as external agents, employ a End users, as external agents, employ a Web (HTTP) interface of Rule Responder Web (HTTP) interface of Rule Responder (currently an API-like browser interface)(currently an API-like browser interface)
Support for multiple external agents Support for multiple external agents (end users) at the same time(end users) at the same time
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Architecture - OverviewArchitecture - Overview
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Rule EnginesRule Engines
Prova (Prolog + Java)Prova (Prolog + Java)
OO jDREW (Object Oriented Java OO jDREW (Object Oriented Java Deductive Reasoning Engine for the Deductive Reasoning Engine for the Web)Web)
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ProvaProva
Prova is mainly used to realize the Prova is mainly used to realize the organizational agents of Rule organizational agents of Rule ResponderResponder
It implements Reaction RuleML for It implements Reaction RuleML for agent interaction (event-condition-agent interaction (event-condition-action rules)action rules)
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OO jDREW OO jDREW
OO jDREW is used to realize theOO jDREW is used to realize thepersonal agents of Rule Responderpersonal agents of Rule Responder
It implements Hornlog RuleML for It implements Hornlog RuleML for agent reasoning (Horn logic rules)agent reasoning (Horn logic rules)
Supports rules in two formats:Supports rules in two formats: POSL: POSL: Positional Slotted presentation Positional Slotted presentation
syntaxsyntax RuleML: RuleML: XML interchange syntaxXML interchange syntax
(can be generated from POSL) (can be generated from POSL)
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Communication MiddlewareCommunication Middleware MuleMule Enterprise Service Bus (ESB) Enterprise Service Bus (ESB)
Mule* is used to create communication Mule* is used to create communication end points at each personal and end points at each personal and organizational agent of Rule Responderorganizational agent of Rule Responder
Mule supports various transport Mule supports various transport protocolsprotocols(e.g. HTTP, JMS, SOAP)(e.g. HTTP, JMS, SOAP)
Rule Responder currently uses HTTP and Rule Responder currently uses HTTP and JMS as transport protocolsJMS as transport protocols
* Mule – The open source SOA infrastructure: http://mulesource.com
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Reaction RuleMLReaction RuleML
Reaction RuleML is a branch of the Reaction RuleML is a branch of the RuleML family that supports actions RuleML family that supports actions and events and events
When two agents need to When two agents need to communicate, each others’ Reaction communicate, each others’ Reaction RuleML messages are sent through RuleML messages are sent through the ESBthe ESB
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Use Case: Symposium Use Case: Symposium Planner Planner
RuleML-20xy SymposiumRuleML-20xy Symposium An organizational agent acts as the An organizational agent acts as the
single point of entry to the symposium single point of entry to the symposium Assists with planning, preparing, and Assists with planning, preparing, and
running the symposium running the symposium Personal agents support chairs of the Personal agents support chairs of the
symposiumsymposium Program Chair, Panel Chair, Publicity Chair, Program Chair, Panel Chair, Publicity Chair,
General Chair, etc.General Chair, etc.
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Online Use Case DemoOnline Use Case Demo Rule Responder:Rule Responder:
http://responder.ruleml.orghttp://responder.ruleml.org
RuleML-2007/RuleML-2008 Symposia:RuleML-2007/RuleML-2008 Symposia:http://ibis.in.tum.de/projects/paw/ruleml-2007http://ibis.in.tum.de/projects/paw/ruleml-2007http://ibis.in.tum.de/projects/paw/ruleml-2008http://ibis.in.tum.de/projects/paw/ruleml-2008
Personal agents:Personal agents:Supporting Panel and Publicity ChairsSupporting Panel and Publicity Chairs
Organizational agent:Organizational agent:Supporting Symposium as a wholeSupporting Symposium as a whole
Online
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Personal Panel Chair Agent Personal Panel Chair Agent Knowledge BaseKnowledge Base
% Sample FOAF-extending rule in POSL syntax:% Sample FOAF-extending rule in POSL syntax:
person(?person, ?role, ?title, ?email, ?person(?person, ?role, ?title, ?email, ?telephone)telephone) :-:-
mailphone(?person, ?email, ?telephone),mailphone(?person, ?email, ?telephone),
role(?person, ?role),role(?person, ?role),
title(?person, ?title).title(?person, ?title).
% Sample FOAF-like facts used by the above rule:% Sample FOAF-like facts used by the above rule:
mailphone(John, [email protected], 1-555-555-5555).mailphone(John, [email protected], 1-555-555-5555).
role(John, Panel Chair).role(John, Panel Chair).
title(John, PHD).title(John, PHD).
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Organizational Organizational Symposium Symposium Agent Agent Knowledge Base (Abridged)Knowledge Base (Abridged)
% Sample Prova-like rule in POSL syntax:% Sample Prova-like rule in POSL syntax:
getContact(?conference_part, ?info, ?getContact(?conference_part, ?info, ?contact) :-contact) :-
person(person(
?contact, ?role, ?title, ?email, ??contact, ?role, ?title, ?email, ?telephone).telephone).
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Sample Message to Organizational AgentSample Message to Organizational Agent
<RuleML xmlns="http://www.ruleml.org/0.91/xsd"<RuleML xmlns="http://www.ruleml.org/0.91/xsd" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.ruleml.org/0.91/xsdxsi:schemaLocation="http://www.ruleml.org/0.91/xsd http://ibis.in.tum.de/research/ReactionRuleML/0.2/rr.xsd"http://ibis.in.tum.de/research/ReactionRuleML/0.2/rr.xsd" xmlns:ruleml2007="http://ibis.in.tum.de/projects/paw#">xmlns:ruleml2007="http://ibis.in.tum.de/projects/paw#">
<Message mode="outbound" directive="query-sync"><Message mode="outbound" directive="query-sync"> <oid><Ind>RuleML-2007</Ind></oid><oid><Ind>RuleML-2007</Ind></oid> <protocol><Ind>esb</Ind></protocol><protocol><Ind>esb</Ind></protocol> <sender><Ind>user</Ind></sender><sender><Ind>user</Ind></sender> <content><content> <Atom><Atom> <Rel>getContact</Rel><Rel>getContact</Rel> <Ind>ruleml2007_Challenge</<Ind>ruleml2007_Challenge</
Ind>Ind> <Ind>update</Ind><Ind>update</Ind> <Var>Contact</Var><Var>Contact</Var> </Atom></Atom> </content></content> </Message></Message> </RuleML></RuleML>
Online
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Architecture - ExecutionArchitecture - Execution
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Architecture - ExecutionArchitecture - Execution
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Architecture - ExecutionArchitecture - Execution
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Architecture - ExecutionArchitecture - Execution
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Architecture - ExecutionArchitecture - Execution
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Sample Message to Publicity Chair Agent (I)Sample Message to Publicity Chair Agent (I) <content><content> <Atom><Atom> <Rel>sponsor</Rel><Rel>sponsor</Rel> <Expr><Expr> <Fun>contact</Fun><Fun>contact</Fun> <Ind>Mark</Ind><Ind>Mark</Ind> <Ind>JBoss</Ind><Ind>JBoss</Ind> </Expr></Expr> <Ind type="integer"><Ind type="integer">500500</Ind></Ind> <Expr><Expr> <Fun>results</Fun><Fun>results</Fun> <Var>Level</Var><Var>Level</Var> <Var>Benefits</Var><Var>Benefits</Var> <Var>DeadlineResults</Var><Var>DeadlineResults</Var> </Expr></Expr> <Expr><Expr> <Fun>performative</Fun><Fun>performative</Fun> <Var>Action</Var><Var>Action</Var> </Expr></Expr> </Atom></Atom> </content></content>
Online
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Sample Message to Publicity Chair Agent (II)Sample Message to Publicity Chair Agent (II) <content><content> <Atom><Atom> <Rel>sponsor</Rel><Rel>sponsor</Rel> <Expr><Expr> <Fun>contact</Fun><Fun>contact</Fun> <Ind>Mark</Ind><Ind>Mark</Ind> <Ind>JBoss</Ind><Ind>JBoss</Ind> </Expr></Expr> <Ind type="integer"><Ind type="integer">50005000</Ind></Ind> <Expr><Expr> <Fun>results</Fun><Fun>results</Fun> <Var>Level</Var><Var>Level</Var> <Var>Benefits</Var><Var>Benefits</Var> <Var>DeadlineResults</Var><Var>DeadlineResults</Var> </Expr></Expr> <Expr><Expr> <Fun>performative</Fun><Fun>performative</Fun> <Var>Action</Var><Var>Action</Var> </Expr></Expr> </Atom></Atom> </content></content>
Online
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ConclusionConclusion
Rule Responder can be used to implement Rule Responder can be used to implement a wide range of use cases that require a a wide range of use cases that require a semi-automated decision layersemi-automated decision layer
The Mule middleware of Rule Responder The Mule middleware of Rule Responder allows platform-independent deployment allows platform-independent deployment of multiple running use cases of multiple running use cases simultaneouslysimultaneously
The system is reusable on all levels:The system is reusable on all levels:Symposium Planner, Rule Responder, Symposium Planner, Rule Responder, POSL, RuleML, OO jDREW, Prova, MulePOSL, RuleML, OO jDREW, Prova, Mule
