Joint International Technology Conference (JIST2011)        Hangzhou, China, December 5, 2011An Ontological Formulation an...
Summary   Introduction   Planning metamodel   OWL formalization   OPM mapping   Inference over the model   Use case ...
Planning Problem   Definition of sequences of actions to reach a desired goal       Automated planning & scheduling in A...
Domain theory – core elements 1/2   Component: physical or logical subsystem of interest for    the planning       Contr...
Domain theory – core elements 2/2   Planning Rule: representation of actions’ causality –    specifies the consequences o...
An OWL2 FormulationCore elements                                                          actionTriggersAction            ...
An OWL2 Formulation      Rule conditions     PlanningRule                               Rule                              ...
Open Provenance Model (OPM)   Model for the tracking of the provenance of artifacts   Three main concepts:              ...
Mapping the planning metamodeland OPMV                                                                opmv:wasDerivedFrom ...
Checking of the domain theories   Meta-model to represent domain theories       Vocabulary       Axioms   It is possib...
Domain theory checkingOrphan elements 1/2                                                                           Orphan...
Domain theory checkingOrphan elements 2/25/12/2011         JIST 2011, Hangzhou, China   12 /16
Inference and automated checkingAction reachability   Reachable action: action with a target role in one or more    plann...
Use case – Pandora   Application in Simulation Learning for decision    making in a scenario of crisis management   Used...
Conclusions and future work   Use of Semantic Web in planning:       Modelling of domain theories       Semi-automated ...
Thank you!      An Ontological Formulation and an OPM profile for              Causality in Planning Applications         ...
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An Ontological Formulation and an OPM profile for Causality in Planning Applications

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An Ontological Formulation and an OPM profile for Causality in Planning Applications

  1. 1. Joint International Technology Conference (JIST2011) Hangzhou, China, December 5, 2011An Ontological Formulation andan OPM profile for Causality in Planning Applications Irene Celino and Daniele Dell’Aglio CEFRIEL – Politecnico di Milano, Italy daniele.dellaglio@cefriel.it
  2. 2. Summary Introduction Planning metamodel OWL formalization OPM mapping Inference over the model Use case – PANDORA Conclusions and future work5/12/2011 JIST 2011, Hangzhou, China 2 /16
  3. 3. Planning Problem Definition of sequences of actions to reach a desired goal  Automated planning & scheduling in AI The task requires a domain theory – a model with the knowledge useful to generate plans  Agents, actions, causal relationships, etc.  Defined by a modeller Our research focus on helping the modeller in checking the coherence and rationality of the domain theory5/12/2011 JIST 2011, Hangzhou, China 3 /16
  4. 4. Domain theory – core elements 1/2 Component: physical or logical subsystem of interest for the planning  Controllable vs Uncontrollable  Agent vs Resource Action: temporally tagged event  Event: an action determined by the planner (related to a controllable component)  Decision: an action taken by an uncontrollable component5/12/2011 JIST 2011, Hangzhou, China 4 /16
  5. 5. Domain theory – core elements 2/2 Planning Rule: representation of actions’ causality – specifies the consequences of actions  Reference Action  Rule Targets: actions that could be “caused” by the reference action  Rule Conditions: requirements on the actions involved in a planning rule, expressed through rule relations:  Temporal conditions  Constraints  Assignments5/12/2011 JIST 2011, Hangzhou, China 5 /16
  6. 6. An OWL2 FormulationCore elements actionTriggersAction Action hasActionValue isActionOf Component hasReferenceAction RuleTarget isRuleEffectActionOf hasReferenceComponent hasRuleTarget PlanningRule Rule ruleTriggersRule hasRuleCondition Condition The whole ontology is available at: http://swa.cefriel.it/ontologies/tplanning5/12/2011 JIST 2011, Hangzhou, China 6 /16
  7. 7. An OWL2 Formulation Rule conditions PlanningRule Rule  Temporal rule relations hasRuleCondition Condition were modelled using rdfs:subClassOf Allen’s Interval Algebra Assignment Constraint Temporal  The three kinds of rule Condition Condition Condition conditions are defined rdfs:subClassOf rdfs:subClassOf extending SPIN vocabulary (SPARQL sp:Let sp:Filter Inferencesp:variable sp:expression sp:expression Notation, http://spinrdf. sp:arg1, org/) ... sp:arg2, ... sp:Function 5/12/2011 JIST 2011, Hangzhou, China 7 /16
  8. 8. Open Provenance Model (OPM) Model for the tracking of the provenance of artifacts Three main concepts: opmv:wasDerivedFrom opmv:wasGeneratedBy opmv:wasopmv:Agent ControlledBy opmv:Process opmv:Artifact opmv:used opmv:wasTriggeredBy OPM Profiles We mapped using the OPM Vocabulary (OPMV) to define an OPM Profile5/12/2011 JIST 2011, Hangzhou, China 8 /16
  9. 9. Mapping the planning metamodeland OPMV opmv:wasDerivedFrom actionTriggersAction Action hasActionValue isActionOf opmv:Artifact Component hasReferenceAction opmv:used RuleTarget opmv:Agent opmv:wasGeneratedBy isRuleEffectActionOf hasReferenceComponent opmv:wasControlledBy opmv:Process hasRuleTarget PlanningRule Rule ruleTriggersRule hasRuleCondition Condition opmv:wasTriggeredBy5/12/2011 JIST 2011, Hangzhou, China 9 /16
  10. 10. Checking of the domain theories Meta-model to represent domain theories  Vocabulary  Axioms It is possible to model domain theories using the ontology Inference processes on domain theories are available Semi-automated checking to the domain theories  Extraction of relevant information from the model for the modeller5/12/2011 JIST 2011, Hangzhou, China 10 /16
  11. 11. Domain theory checkingOrphan elements 1/2 Orphan Extract from the planning component model the orphan elements: Components C2  Components not involved in C4 C5 any Action C1 C3  Actions not involved in any Planning Rule A4 A1 Actions Allow the modeller to check A2 A3 potential lacks or A5 shortcomings Planning rules P2 P1 Orphan action5/12/2011 JIST 2011, Hangzhou, China 11 /16
  12. 12. Domain theory checkingOrphan elements 2/25/12/2011 JIST 2011, Hangzhou, China 12 /16
  13. 13. Inference and automated checkingAction reachability Reachable action: action with a target role in one or more planning rules Modeller is interested in finding:  Unreacheble actions: actions generated by controllable components that are never target  Actions triggered by the unrecheable action P2 An P1 Pn A1 A2 A3 triggersUnreachable Action: A1 referenceA1 dependent actions: A2, A3 ... An target5/12/2011 JIST 2011, Hangzhou, China 13 /16
  14. 14. Use case – Pandora Application in Simulation Learning for decision making in a scenario of crisis management Used in the Pandora EU FP7 project  Realization of a platform for the training of gold commanders  Planning is used to simulate learning sessions  Support at the design time for the building of domain theories Additional info on: http://pandoraproject.eu5/12/2011 JIST 2011, Hangzhou, China 14 /16
  15. 15. Conclusions and future work Use of Semantic Web in planning:  Modelling of domain theories  Semi-automated approach to verify the modelling:  Tracking causality  Check of elements involvement  … Future work  In-depth evaluation  Relation with PDDL  Analysis of executed plans5/12/2011 JIST 2011, Hangzhou, China 15 /16
  16. 16. Thank you! An Ontological Formulation and an OPM profile for Causality in Planning Applications Daniele Dell’Aglio CEFRIEL – ICT Institute of Politecnico di Milano, Italy e-mail: daniele.dellaglio@cefriel.it web: http://www.cefriel.it5/12/2011 JIST 2011, Hangzhou, China 16 /16

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