Case Adaptation Sources: –Chapter 8 – –

Adaptation New problem Selected case Adaptation knowledge Solution

Classes of Adaptation No-adaptation Transformational Analogy  Substitution Adaptation  Feedback based  constraint based  Compositional adaptation Generative Solution Adaptation  Transformational Analogy  Derivational Analogy

No Adaptation For classification/diagnosis tasks If C is the NN for a new problem P then class(P)  class(C) If {C 1,…,C k } are the k-NN for a new problem P then Class(C)  F({C 1,…,C k }) For example: F({C 1,…,C k }) = “majority class among {C 1,…,C k }”

Substitution Adaptation Let C = (P,S); A problem P and a solution S Adaptation problem:  Given  A problem P’  A case C such that P is similar to P’  Search a substitution  such that  (S) solves P’   corresponds to an application of a rule transforming parts of the case (so it is not a substitution in the traditional sense)

Example Support for PC sale: Cases are configuration episodes of PCs User specifies his/hers requirements System selects best PC (e.g., using CCBR) and change some components Example rules (Substitutional Adaptation): If (query.application = ‘database’ and case.diskSpace < 2GB) then target.diskSpace  4GB

Example (2) Example rules (Substitutional Adaptation): If (query.application = ‘games’ and case.application  ‘games’) then AddObject target.addJoystick AddObject target.addSoundCard Other rules to configure joystick and sound

Substitutional Feedback-based Car type: sport Color: red Seating: 2 Valves: 48 Type: 5.7L Model name: name1 Price: 200,000 Year: 2003 Feedback: not successful Cause: price is too high Car type: sport Color: red Seating: 2 Valves: 48 Type: 5.7L Model name: name1 Price: 200,000 Year: 2003 Feedback: successful Car type: sport Color: red Seating: 2 Valves: 40 Type: 3.6L Model name: name 2 Price: 150,000 Year: 2000 Feedback: successful Adapt CaseC (adapted) CaseA (new) CaseB (old) Retrieve Copy Rule: if price is too high then model  previous model

Substitutional Constraint-based Case ID: 123 Speed: high Price: middle Usage: sport Antitheft performance: high Model Name: Toyota Sedan 07 Price: 10,500 Antitheft system: Product A Case ID: 456 Speed: high Price: middle Usage: sport Antitheft performance: middle Model Name: Toyota Sedan 07 Price: 10,500 Antitheft system: Product A Case ID: 123 Speed: high Price: middle Usage: sport Antitheft performance: high Model Name: Toyota Sedan 07+ Price: 11,000 Antitheft system: Product B CaseA (new) CaseB (old) Retrieve Copy adapt CaseC (adapted) Rule: if need higher Antitheft performance and Antitheft System = product A then Antitheft System  product B Price  Price + 500

Compositional Adaptation Let C = (P,S); A problem P and a solution S Adaptation problem:  Given  A problem P’  A case C such that P is similar to P’  Search a sequence of substitutions  1, …,  n such that: S’ is a solution for P’ (P,C) …(P’,S’) 11 22 nn

Adaptation Operators (2)  Uses rule-based systems during adaptation  Roles of operators/rules: General knowledge about the domain (P,C) …(P’,S’) 11 22 nn Adaptation knowledge