1. Coping with Exceptions in Agent-Based Workflow Enactments Frank Guerin University of Aberdeen

2. Coping with Exceptions in Agent-Based Workflow Enactments Frank Guerin University of Aberdeen Joey Sik-Chun Lam, Frank Guerin, Wamberto Vasconcelos, and Timothy J. Norman

3. Business Processes

4. Agents

5. Business Processes AgentsSemantic Web Languages

6. Business Processes AgentsSemantic Web Languages Workflow = The automation of a business process, in whole or part, during which documents, information or tasks are passed from one participant to another for action, according to a set of procedural rules (WfMC)

7. Business Processes AgentsSemantic Web Languages Workflows  In human organisations (business, health)  Intra / inter  Automated by computer  e.g. Calling Web services  Existing Workflow Management Systems Taverna Kepler Centralised + Rigid  limited exception handling

8. Business Processes AgentsSemantic Web Languages Business Processes  Workflow  Existing systems rigid

9. Business Processes AgentsSemantic Web Languages Business Processes  Workflow  Existing systems rigid

10. Business Processes Semantic Web Languages Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions

11. Three Level Architecture Organisation level  Mostly static Coordination level  Dynamic, Communication, Some planning Service level  Also some intelligence, composition, matching

12. Exceptions in Agent-based Workflow Organisation level:  Organisational structure makes it impossible  e.g. change in environment Coordination level:  e.g. some role empty  Alternate pathways ? Service level:  e.g. Web service is unavailable  Alternative service (semantic matching)  Handle at higher level(Aldewereld et al.)

13. Exceptions in Agent-based Workflow Organisation level:  Organisational structure makes it impossible  e.g. change in environment Coordination level:  e.g. some role empty  Alternate pathways ? Service level:  e.g. Web service is unavailable  Alternative service (semantic matching)  Handle at higher level(Aldewereld et al.)

14. Exceptions in Agent-based Workflow Organisation level:  Organisational structure makes it impossible  e.g. change in environment Coordination level:  e.g. some role empty  Alternate pathways ? Service level:  e.g. Web service is unavailable  Alternative service (semantic matching)  Handle at higher level(Aldewereld et al.)

15. Exceptions in Agent-based Workflow Organisation level:  Organisational structure makes it impossible  e.g. change in environment Coordination level:  e.g. some role empty  Alternate pathways ? Service level:  e.g. Web service is unavailable  Alternative service (semantic matching) (Aldewereld et al.) Existing Techniques

16. Exceptions in Agent-based Workflow Organisation level:  Organisational structure makes it impossible  e.g. change in environment Coordination level:  e.g. some role empty  Alternate pathways ? Service level:  e.g. Web service is unavailable  Alternative service (semantic matching) (Aldewereld et al.) No Existing Techniques

17. Exceptions in Agent-based Workflow Organisation level:  Organisational structure makes it impossible  e.g. change in environment Coordination level:  e.g. some role empty  Alternate pathways ? Service level:  e.g. Web service is unavailable  Alternative service (semantic matching) (Aldewereld et al.) Workflow tasks must be meaningful

18. Business Processes Semantic Web Languages Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions

19. Business Processes Semantic Web Languages Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions → Workflows Flexible Robust

20. Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions → Workflows Flexible Robust Semantic Web Languages  Organisational Knowledge  Tasks  Roles  Norms  Powers

21. Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions → Workflows Flexible Robust Semantic Web Languages  Organisational Knowledge  Tasks  Roles  Norms  Powers Not yet… later SWRL DL-safe rules

22. Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions → Workflows Flexible Robust Semantic Web Languages  Organisational Knowledge  Tasks  Roles  Norms  Powers  Reasoners  Standard

23. Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions → Workflows Flexible Robust Semantic Web Languages  Organisational Knowledge  Tasks  Roles  Norms  Powers  Reasoners  Standard

24. Workflow Example (only shows external messages)

25. Workflow Example Failure happens at this point

26. Workflow Example Failure happens at this point Stage 5: query_expertise (useful) –Authorise –or Reject

27. Modeling the Institution (Organisation)  Institutional Facts F =

28. Modeling the Institution (Organisation)  Institutional Facts F = State of Affairs Roles World facts Power Prohibition Obligation

29. Modeling the Institution (Organisation)  Institutional Facts F = State of Affairs Roles World facts Power Prohibition Obligation Predicates, Clauses

30. Modeling the Institution (Organisation)  Institutional Facts F = State of Affairs Roles World facts Power Prohibition Obligation Rules (speech acts or events modify F )

31. Modeling the Institution (Organisation)  Institutional Facts F = State of Affairs Roles World facts Power Prohibition Obligation Rules (speech acts or events modify F ) FnFn Speech act F n+1

32. Institutional Facts  power(hod, allocate_task (Ag,[Task,Time_limit])) if role (Ag,cs_dept_staff)  power (hod, assign_temp role (college_staff,[Ag,hod,Duration])) if role (Ag,cs dept_staff) and role (Ag,professor) and Duration 21:00:00  power (hod, suspend_role (college staff,[Ag,Role,Duration])) if role (Ag,cs dept_staff)

33. Institutional Facts  power (hoc, assign_role (college staff,[Ag,hod])) if role (Ag,cs_dept_staff) and role (Ag,professor)  power (hoc, assign_power (college staff,[Ag,Power])) if role (Ag,college_staff)  power (hod, authorise_purchase (secretary,Item))

34. Institutional Facts  obliged (bob, complete_task (“upgrade webserver”),“05-June-12:00”, 103)  obliged (fred, complete_task (“submit paper to conference”),“09-Sept-18:00”, 103)  prohibited (hoc, assign_power (college_staff,[hoc,Power]),103)

35. Simple Procedural Interpretation UPDATE-INSTITUTIONAL-FACTS 1.Input: speech act (Sender, Receiver, Perf., Content) 2.Check if Sender empowered If not, discard the act and exit 3.Check if Sender prohibition If not, go to the next step; If so, apply the specified sanction. 4.Check if Sender obligation If so remove obligation 5.Process the act as normal (i.e., follow the rules specified for the act)

36. Overview

37. Some Axioms from the Ontology HoD ⊑ ¬ HoC ∃ supervises.( ∃ doesProject.Project) ⊑ ¬ ∃ marksProject.Project Student ⊑ ≥ 1 takesCourse

38. Some Axioms from the Ontology ∃ teaches.Course v ∃ hasExpertise.Course Professor(dave) teaches(dave,Robotics) ⊤ ⊑ ∀ teaches.Course Query_expertise ⊑ ∃ doneBy.(Person ⊓ ∃ hasExpertise.Expertise) Equipment(?q) ^ Expertiment(?x) ^ isNeededBy(?q,?x)  is_appropriate.equipment(?q,?x)

39. Some SPARQL Queries Prefix uni: SELECT ?manager WHERE { “HoD” uni:managedBy ?manager } Prefix uni: SELECT ?person WHERE { ?person uni:hasExpertise “Robotics” }

40. Exception Handling Routine Upon the failure of a message delivery  Query ontology to get manager of intended recipient  Manager inspects tasks in workflow at this place  Find a suitable agent who can perform them (from ontology)

41. Exception Handling in Example Upon the failure of a message delivery  Query ontology to get manager of intended recipient SPARQL query finance secretary finds HoC (manager)  Manager inspects tasks in workflow at this place  Query expertise to see is equipment useful  Authorise or reject proposal  Requirements:  Expertise in robotics  Power to approve purchases  Find a suitable agent who can perform them (SPARQL query + assign power)

42. Some SPARQL Queries Prefix uni: SELECT ?manager WHERE { “HoD” uni:managedBy ?manager }

43. Exception Handling in Example Upon the failure of a message delivery  Query ontology to get manager of intended recipient SPARQL query finance secretary finds HoC (manager)  Manager inspects tasks in workflow at this place  Query expertise to see is equipment useful  Authorise or reject proposal  Requirements:  Expertise in robotics  Power to approve purchases  Find a suitable agent who can perform them (SPARQL query + assign power)

44. Exception Handling in Example Upon the failure of a message delivery  Query ontology to get manager of intended recipient SPARQL query finance secretary finds HoC (manager)  Manager inspects tasks in workflow at this place  Query expertise to see is equipment useful  Authorise or reject proposal  Requirements:  Expertise in robotics  Power to approve purchases  Find a suitable agent who can perform them (SPARQL query + assign power)

45. Exception Handling in Example Upon the failure of a message delivery  Query ontology to get manager of intended recipient SPARQL query finance secretary finds HoC (manager)  Manager inspects tasks in workflow at this place  Query expertise to see is equipment useful  Authorise or reject proposal  Requirements:  Expertise in robotics  Power to approve purchases  Find a suitable agent who can perform them (SPARQL query + assign power)

46. Exception Handling in Example Upon the failure of a message delivery  Query ontology to get manager of intended recipient SPARQL query finance secretary finds HoC (manager)  Manager inspects tasks in workflow at this place  Query expertise to see is equipment useful  Authorise or reject proposal  Requirements:  Expertise in robotics  Power to approve purchases  Find a suitable agent who can perform them (SPARQL query + assign power)

47. Some SPARQL Queries Prefix uni: SELECT ?person WHERE { ?person uni:hasExpertise “Robotics” }

48. Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions → Workflows Flexible Robust Semantic Web Languages  Organisational Knowledge  Tasks  Roles  Norms  Powers  Reasoners  Standard

49. Business Processes  Workflow  Existing systems rigid Agents  Distributed  Intelligent  Autonomous  Cope with exceptions → Workflows Flexible Robust Semantic Web Languages  Organisational Knowledge  Tasks  Roles  Norms  Powers  Reasoners  Standard

50. Exception Handling in Example  Klein and Dellarocas  Doctor  diagnoses agents illness and prescribe treatment  Build expert repository of handling procedures  Buhler and Vidal  Slide agent between Web service and workflow engine  Singh  Commitments (high level meaning)  Mallya and Singh library of sets of runs