An Ontological Formulation and an OPM profile for Causality in Planning Applications
1. Joint International Technology Conference (JIST2011)
Hangzhou, China, December 5, 2011
An Ontological Formulation and
an OPM profile for Causality in
Planning Applications
Irene Celino and Daniele Dell’Aglio
CEFRIEL – Politecnico di Milano, Italy
daniele.dellaglio@cefriel.it
2. Summary
Introduction
Planning metamodel
OWL formalization
OPM mapping
Inference over the model
Use case – PANDORA
Conclusions and future work
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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
theory
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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 component
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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
Assignments
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6. An OWL2 Formulation
Core 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/tplanning
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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
Inference
sp:variable sp:expression sp:expression Notation, http://spinrdf.
sp:arg1,
org/)
... sp:arg2, ...
sp:Function
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8. Open Provenance Model (OPM)
Model for the tracking of the provenance of artifacts
Three main concepts:
opmv:wasDerivedFrom
opmv:wasGeneratedBy
opmv:was
opmv:Agent ControlledBy
opmv:Process opmv:Artifact
opmv:used
opmv:wasTriggeredBy
OPM Profiles
We mapped using the OPM Vocabulary (OPMV) to define
an OPM Profile
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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
modeller
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11. Domain theory checking
Orphan 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
action
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13. Inference and automated checking
Action 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
triggers
Unreachable Action: A1 reference
A1 dependent actions: A2, A3 ... An target
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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.eu
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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 plans
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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.it
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