1. Integrating Agents, Ontologies, and Semantic Web Services for Collaboration on the Semantic Web Michael Stollberg and Thomas Strang DERI – Digital Enterprise Research Institute First International Symposium on Agents and the Semantic Web AAAI Fall Symposium Series 2005 Arlington, Virginia, 05 November 2005

2. 2 Content 1.Motivation and Aims –Semantic Web vision = automated collaboration support on the Web –Aim = technical realization 2.Framework –Conceptual Model –Elements (Description and Usage) Model of Agency “Collaboration Services” Goal-driven Architecture 3.Semantic Collaboration Management –Collaboration Establishment –Collaboration Execution 4.Conclusions

3. 3 Motivating Example LMPD Agent A(P) Goal: plan[ - med. treatment for M - chauffeur(P) - consistent with calendar(P)] Plan: - check plan from A(L) - if OK, then book else: revise plan Agent A(L) Goal: plan[ - med. treatment for M - chauffeur(P)] Plan: 1) find suitable doctor 2) coordinate chauffeur(P) med. info service calendar service transport info serv. owns O-personO-medicalO-date&timeO-transport Agent A(D) Goal: offer[ - med. treatment - appointement] Plan: 1) find customer 2) book appointement owns book app. service doctor information (website) ontology usage (also for agents, omitted here) 1:need medical treatment 2: inform, chaffeur(P) 3a: assign goal 3b: make / find plan 3b: make / find plan 3a: assign goal Xb: make / find plan Xa: assign goal 4:find doctor uses provides 5:inform, plan 6:revise plan 7:book appointment interact uses 8: add plan from: Berners-Lee, T.; Hendler, J.; Lassila, O.: The Semantic Web. A new form of Web Content that is meaningful to computers will unleash a revolution of new possibilities. In: Scientific American 9(5), May 2001.

4. 4 Automated Collaboration Support on the Semantic Web In fact, the Semantic Web vision proclaims seamless and automated collaboration support on the Web –collaboration = cooperative interactions of individuals for achieving complex objectives or objectives that require purposeful cooperation –... is a constituting principle of (human) society –… the “Semantic Web” shall provide sophisticated support for this Base Technologies: –Software Agents personal assistants / electronic representatives –Ontologies semantic interoperability –(Semantic) Web Services computation over the Web Technology for Collaboration Support needs to: –reflect the epistemology of collaboration –integrate base technologies properly –comply with technical requirements

5. 5 Our Approach Agents as electronic representatives of collaborating real-world entities use: –(Semantic) Web resources as information resources –(Semantic) Web services as means for automated communication & cooperation Semantic Web Service technologies for collaboration management Semantic descriptions as extension of WSMO Design Principles (combining Agent & Web technology for collaboration support) 1.Agents as Symmetric Collaboration Entities 2.Ontologies as Data Model 3.Web Compliance 4.Goal Driven Architecture 5.Semantic Collaboration Management 6.Strict Decoupling and Strong Mediation 7.Maximal Automation

6. 6 Conceptual Model Agent B Goal Instance Agent A Goal Instance has(1,n) compatible goals = collaboration partners automated collaboration execution Domain Knowledge uses(1,n) has(1,n) uses(1,n) Collaboration Service Web Service Goal Template Repository Service Repository Collaboration Service Web Service Owner goal assignment service discovery owns Ontology

7. 7 Model of Agency Agent = electronic representative of a real world entity involved in collaborative interactions –receives task from owner (objectives represented as Goals) –uses “Collaboration Service” as facility for participating in collaborations automatically executed over the Semantic Web –controls own collaboration behavior by using services for collaboration management Goal-driven Collaborative Interface Agents –Reactivity & Proactiveness via interaction with owner and other agents –Autonomy as self-controlled collaboration behavior –Social Abilities as purposeful information interchange & communication via Collaboration Services Semantic description –‘data container’ of owner and collaboration information –ontologies used as data model

8. 8 Agent Semantic Description Agents electronic representative of real world entity that wants to achieve an objective by collaborative interaction with other real world entities Class agent hasNonFunctionalProperties type nonFunctionalProperties importsOntology type ontology usesMediator type ooMediator owner type owner collaboration type collaboration history type collaboration Class owner hasNonFunctionalProperties type nonFunctionalProperties owner type instance preference type axiom policy type axiom serviceUsagePermission type service Class collaboration hasNonFunctionalProperties type nonFunctionalProperties goal type goal single-valued service type service

9. 9 Collaboration Services Web Service used by Agents to participate in collaborations automatically executed over the (Semantic) Web –a computational facility accessible over the Web that provides a functionality useful for an agent to automate collaboration execution –can provide very simply or arbitrary complex functionality –can “talk” to other agents via their collaboration services dynamically detected (possibly composed) and consumed by an Agent wrt / via an Goal Instance –each objective is solved in a different collaboration –agent discovers suitable Collaboration Services (Web service discovery), possibly determines composite Collaboration Service –Goal Instance +Agent data container = input for service execution Semantic description: –extended WSMO Web service description –“orchestration” defines interaction behavior with other services / resources for achieving functionality

10. 10 Collaboration Service Description & Usage Agent A postcondition Goal Instance effect submission result Service Implementation (not of interest for service description) Capability Client-Interface WS Orchestration Agent B Service Implementation (not of interest for service description) WS Orchestration Client-Interface (1) = functional suitability (2) = service usage (3) = service interaction (1) (2) (1) (2) (3) preferences postcondition Goal Instance effect submission result preferences WS nFP Capability nFP

11. 11 Collaboration Service Description Collaboration Services facility an agent uses for participating in an automatically executed collaboration; interacts with other agents and utilizes Semantic Web resources via its orchestration Class collaborationService is-a wsmoService hasNonFunctionalProperties type nonFunctionalProperties importsOntology type ontology usesMediator type ooMediator hasCapability type capability single-valued hasSharedVariables type sharedVariable hasPrecondition type axiom hasAssumption type axiom hasPostcondition type axiom hasEffect type axiom hasInterface type interface clientInterface type serviceInterfaceDescription orchestration type serviceInterfaceDescription Class serviceInterfaceDescription sub-Class wsmoServiceInterface hasNonFunctionalProperties type nonFunctionalProperties importsOntology type ontology usesMediator type ooMediator hasVocabulary type concept_in, concept_out, concept_controlled hasState type ontology hasGuardedTransition type if (condition) then rule // rule = if-then rule | add-delete-update(fact) | forAll / choose (var) rule

12. 12 Goals Goal-driven Architecture –users specify objectives as Goal Instances and assign this to their agent –goal creation by instantiation of Goal Templates –each objective is solved in a different collaboration > Goals are the central element of the system Goal = semantic description of an user’s objective that carries all information needed for automated collaboration execution via Collaboration Services –user objective as “final desired state” –constraints on goal resolution process –preferences / policies on: collaboration partners, services, time –Collaboration Service usage by Goal Instance + Agent data container semantic description: –extended WSMO Goal description –Management by Goal Templates, Goal Instances, Goal Ontologies

13. 13 Goal Templates and Instances Goal Template -schematic goal description oschema of desired final state oconstraints on resolution process (integrity constraints on states) -pre-defined at “design time”, maintained by “ administrator Goal Instance -concrete objective specification as Goal Template instantiation oproper semantic refinement of its Goal Template wrt. final desired state oadditional information for service usage -created at runtime by users (agent owners) or other agents after resolution, a Goal Instance can become a Goal Template

14. 14 Goals Semantic Description Goal Template predefined schema of user objective (WSMO 1.0 goal plus constraints) Class goalTemplate subClassOf wsmov1.0Goal hasNonFunctionalProperties type nonFunctionalProperties importsOntology type ontology usesMediator type {ooMediator, ggMediator} hasPostcondition type axiom hasEffect type axiom hasConstraint type axiom Goal Instance concrete objective assigned to an agent (instantiated Goal Template, client for service usage) Class goalInstance sub-Instance goalTemplate hasNonFunctionalProperties type nonFunctionalProperties hasPostcondition type axiom hasEffect type axiom hasConstraint type axiom hasSubmission type instance hasResult type instance goalResolutionStatus type goalResolutionStatus

15. 15 Goals Ontologies -Goal Ontologies for efficient management: oNodes = Goals, Arcs = ggMediators that denote “functional correspondence” ocomputed by Δ = explicit logical difference between final desired states GI {S 1,S 2,S 3 } {S 2,S 3 } GT-1 Book Flight GT-2 Book Flight (Star Alliance) subsume {S 3 } GT-3 Book Hotel subsume {S 5,S 8 } {S 2,S 3,S 5, S 8 } GT-4 Book US-Trip (flight + hotel) subsume GI {(S 3, S 8 )} {(S 3,S5),(S 3,S 8 )} composition

16. 16 Collaboration Management Partner Discoverer Service Discoverer Choreography Discoverer GI {GI} GI {S} boolean {S} Collaboration (preliminary) (A i (G 1, {S} 1 ), A 2 (G 2, {S} 2 ),..) Goal Instance Agent (A i (G 1, {S} 1-reduced ), A 2 (G 2, {S} 2-reduced ),..) Goal Instance … separately for each GI each possible service combination Agent Collaboration (final) Collaboration Executor each collaborationgoal resolution for the goal of each collaboration partner goal resolution for the goal of each collaboration partner controlled individually by each agent, functional components as Web Services

17. 17 Collaboration Management Components Collaboration Establishment applying “conventional” Semantic Web Service techniques Partner Discovery = find agent with compatible goal –compatible final states of Goal Instances of agents Service Discovery = find usable Collaboration Service –facility for participating in automated collaboration execution –goal final state <> service post-state ^ submission <> service pre-state –composition as sub-task of service discovery Choreography Discovery = valid Collaboration Service interaction –orchestration compatibility of Collaboration Service of collaborating agents –existence of a valid interaction protocol for all needed interactions Collaboration Execution execute collaborations as Web Service interaction: –feasibility determination (availability of resources, duplication handling) –monitors & controls execution

18. 18 Partner Discoverer Architecture GI i Action-Resource Ontology DiscoveryResult sets of compatible Goal Instances (2) GG Matcher Discovery Request initiating Goal Instance GT i (1) Cooperation Knowledge Filter GT g GI g instanceOf instanceOf, status = ‘open’ Action Compatibility

19. 19 Service Discoverer Architecture Discovery Request Goal Instance Discovery Result usable Services Service Repository Discovery Result (intermediary) Service Filter (2) GIS Matcher GI i GT i instanceOf (1) Pre-Selector Action Equality

20. 20 Choreography Discoverer Architecture Discovery Request set of services {S} Discovery Result Boolean (service compatibility) (2) SC comm Checker Choreography Description Translator (1) SC info Checker WSDL2StateSignBPEL2ASM yes no

21. 21 Conclusions Framework for Collaboration on the Semantic Web –agents, goals, Web Services “integrated” for collaboration support –SWS technologies for –prototype implementation in Semantic Web Fred (SWF) Important Aspects –Model of Agency –Collaboration Services –Goal-driven Architecture –Semantic Collaboration Management Lessons Learned –core (reasoning) tasks are the same in agents and SW / SWS –rationale agent paradigm = determine best next action for achieving goal –(Semantic) Web Service = determine complete interaction model before execution => which one is “better”, i.e. more applicable

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