1
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2
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3
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- Conclusions sanctioned do not
depend on how executed, e.g., forward chaining has same semantics as
backward chaining
- “Reaction” rules, that perform
side-effectful actions, have a semantics which cleanly extends the basic
case of rules that do not.
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4
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- Kernel based on logical KR
- Semantics, syntax,
layering: for that kernel
- Rudimentary rule
management: e.g., queries,
answers, premises, conclusions, updates to premises, ruleset
definition, importation of rules, simple versioning, simple provenance
- Use Cases from Business Processes, Services
- Policies, in particular
- Support Semantic Web Services
requirements, in particular
- Integrate Rules and Ontologies
- Interoperate with OWL, in
particular
- Represent Ontologies as Rules,
in particular
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5
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- Semantic Web
- general, using XML and/or RDF
encoding
- RDF- and OWL-centric, in
particular
- Logic Program based, in
particular
- Business Rules
- general, based on existing
rule-based
- Production Rules, in particular
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6
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- Declarative Logic Programs expressiveness including
- 1. Datalog Horn LP (N-ary predicates supported)
- 2. + scoped default negation
applied to atoms
- a. simple extensional
- b. more general (allowing
inferential chaining to establish the
-
atom in question -- subset of, or full,
-
Well Founded semantics)
- 3. + procedural attachments
(external calls)
- a. actions
(side-effectful – external)
- b. tests
(side-effect-free queries)
- 4. + logical functions, incl.
for object creation, skolemization
- a. limited initially
(to ensure finite/tractable forward inferencing)
- b. more general
(e.g., for backward chaining, “sugar” features)
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7
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- Most other wish-list features
- can be expressively reduced to
this core KR abstraction, for which Situated Ordinary Logic Programs can
provide the semantics theory
- OWL: large subset, Þ
- OWL ontology integration via overlap of LP with
Description Logic
- (e.g., use Description
Logic Programs V2,
-
with integrity constraints, skolemization, equality, passing of
derived facts)
- SWRL: large subset
- Production Rules cf. PRRuleML:
large subset (Production
-
Logic Programs)
- Decision trees
- Decision tables
- “Sequential” rules cf. PRR: [**probable,
need to understand better]
- Prolog: the pure subset (which is
large)
- SQL relational databases: large
subset (incl. all core)
- Event-Condition-Action rules:
large subset
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8
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9
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- Most other wish-list features
- can be expressively reduced* to
this core KR abstraction, for which Situated Ordinary Logic Programs can
provide the semantics theory
(* with tractability, known techniques).
- E.g., much or all of the expressiveness in the following.
- RDF facts
- Frame syntax
- Slotted syntax
- Lists
- (N-ary predicates if restrict core to 2-ary)
- RDFS-DL simple ontologies
- Datatyping: basic
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10
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- “Else” part of if-then-else
- Courteous prioritized defaults,
- incl.
declarative priorities, limited strong/classical negation,
-
prioritized conflict handling, paraconsistency robustness
- Default inheritance cf. Object Oriented programming, “frame” languages
- “Hilog” – quasi higher order syntactic sugar
- Lloyd-Topor
- Integrity constraints that report violations
- Anonymous existentials, blank-nodes, limited skolemization
- “Crud” – create update delete, cf. Production Rules (restricted)
- “Assert”, and basic “retract”, cf. Production Rules (restricted)
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11
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- Reification, basic
- User equality, basic aspects
- Equations, basic
- Built-ins (side-effect-free functions/operators, read/write)
- Access to surrounding object-oriented data environment, cf. OO
Production Rules
- Ontological context translation & mediation
- Contextual selection conditions for whole rulesets
- “Rules flow”: some (e.g., sequencing of rule groups)
- … probably some more things we forgot to list here …
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12
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13
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- subsumes (expressively)
- layers-on (makes use of)
- overlaps-with
(expressively)
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14
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- “Sugar-enhanced” Languages can be translated into the kernel.
- I.e., Sugar Features can be implemented/supported via translators
- Including as “best practice”, etc.
- Could consider doing some of them as part of WG proper
- E.g., basic set of datatypes
- … But it’s not as crucial
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15
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- Abstract syntax
- Semantics
- Layering definitions: e.g.,
Datalog Horn layer
- Concrete syntax:
- Markup syntax in XML
- RDF (e.g., RDF/XML)
- Human-readable presentation (non-XML) syntax
- UML/MOF metamodel
- Some light ontology about rudimentary rule management, incorporated into
the above
- E.g., to enable representing provenance, or expressive restrictions
met, about a particular rulebase
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16
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- Policies: authorization,
contracting, security, privacy, monitoring, advertising, regulations,
governance, …
- Validation: integrity,
notification, …
- Business Processes, Workflows, Protocols, …
- Process modeling: Abstract State
Machines, Pi-Calculus, …
- Semantic Web Services
- Ontologies
- Mediation: map between
ontologies/contexts
- …
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