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CBR matching & brokering IIIA-CSIC IBROW. Framework UPML components as cases Retrieved by CBR constructs in NOOS UPML meta-ontology Object language Describes.

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Presentation on theme: "CBR matching & brokering IIIA-CSIC IBROW. Framework UPML components as cases Retrieved by CBR constructs in NOOS UPML meta-ontology Object language Describes."— Presentation transcript:

1 CBR matching & brokering IIIA-CSIC IBROW

2 Framework UPML components as cases Retrieved by CBR constructs in NOOS UPML meta-ontology Object language Describes CBR properties Concept language Feature logics Similar to description logics (aka )

3 Component matching UPML components are cases in memory We can query the memory Subsumption (query ≤ case) How do we generate queries? Configuration program (“Broker”) Receives a “user consult” for a system Generates queries for particular components in memory Classical search space program Knows about UPML

4 Matching Consult: precond+postcond+models+I/O For a given task T Retrieve PSM (CBR subsumption retrieve): T.postcond ≤ PSM.postcond Filter retrieved PSMs (subsumption filtering) PSM.precond ≤ T.precond Input & Outputs of T & PSM match Goal: find configuration (state) where consult is satisfied

5 S&S Broker Broker understands 2 things UPML Object language Broker is a P. Solver for OL OL=constraints => Broker=SAT solver OL= FOL => Broker=theorem prover S&S broker OL = language for cases in CBR Broker= search technique

6 Components for CAT-CBR

7 Case-base of configured apps

8 Search & Subsume Broker Search thru state space State represents properties of a partially instantiated configuration UPML: understands goals & assumptions Concept language: Subsumption of concept expressions

9 S&S Broker strategies Depth first (shown Stanford) S&S Broker Best first (shown here) CBR Broker Sorting = case-based similarity

10 State Goals Assumptions Knowledge Met-goals Met-assumptions Open-knowledge Used-knowledge PSM-hypothesis Open-tasks Tasks PSMs

11 A sepecification of state

12 A CONFIGURATION CASE

13 Knowledge for search Initial-state: consult->state Successor: State-> State s Combiner: States->Ordered- States Case-based similarity to order states Else order by depth or breadth Goal-state: State ->Boolean Finalize: State->Configuration

14 A configuration

15 New state, new hypothesis N possible PSMs for a task N new hypothesis, N ne w states

16 CBR configuration as BestFirst

17 Specifying a CBR application

18 Configured CBR application

19 Conclusions CBR balances memory vs. search New configuration is also a case With “compiled” goals & assumptions S&S Broker can retrieve config (config = case) Separate configuration from requirement acquisition CBR broker: adapting “similar” configs to user-posed problems


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