Case-Based Solution Diversity

1. Case-Based Solution Diversity Alexandra Coman HéctorMuñoz-Avila Dept. of Computer Science & Engineering Lehigh University • Sources: • cbrwiki.fdi.ucm.es/ • www.iiia.csic.es/People/enric/AICom.html • www.cse.lehigh.edu/~munoz/CSE335/ • www.aic.nrl.navy.mil/~aha/slides/ • http://www.csi.ucd.ie/users/barry-smyth • http://www.csi.ucd.ie/users/lorraine-mcginty

2. Outline • Lehigh University • The InSyTe Laboratory • Overview of Case-Based Reasoning • Similarity • Retrieval • Adaptation • Conversational Case-based reasoning • Diversity versus Similarity • General versus Episodic Knowledge • Final Remarks

3. Synthetizing Diversity • Showcasing diverse solutions: success story in recommender systems (Smyth, Burke, McGinty …) • Plan diversity: • Definition of the problem: quantitative vsqualitiative (Myers, AAAI-01) • Generating two or more quantitative different plans for same problem (Srivastava et al, IJCAI-07) • Synthetizing diversity: • Case-based retrieval and adaptation from plan library (Coman& Munoz-Avila, ICCBR-10; 11 – under review ) • Generating two or more qualitatively different plans for same problem (Coman & Munoz-Avila, AAAI-11) • Our common solution: • S: diverse solutions so far, s: candidate solution, P: new problem sim(s,P) + relativeDiversity(s,S) • What changes: S, s, P, sim(), D(s,s’) 11

4. Research Program: Synthetizing Diversity preliminary work: Plan Diversity Case-based plan diversity sim(s,P) + relativeDiversity(s,S) New insight: sim(s,P) + relativeDiversity(s,S) + cost(s) Proposed idea: • Representation scope of using D() versus qualitative diversity • Trade-offs of solution: • Diversity versus quality • Diversity versus generation • Diversity in other paradigms: search (A*) Research topics: Danger: don’t want it to be a planning proposal

5. Focus Point: Diversity in CBR

6. Query Available case Similar case Traditional Retrieval Approach • Similarity-BasedRetrieval • Select the k most similar items to the current query. • Problem • Vague queries. • Limited coverage of search space in every cycle of the dialogue. C2 C3 C1 Q

7. Query Available case Retrieved case Diversity Enhancement • Diversity-EnhancedRetrieval • Select k items such that they are both similar to the current query but different from each other. • Providing a wider choice allows for broader coverage of the product space. • Allows many less relevant items to be eliminated. C1 Q C2 C3

8. Dangers of Diversity Enhancement • Leap-Frogging the Target • Problems occur when the target product is rejected as a retrieval candidate on diversity grounds. •  Protracted dialogs. • Diversity is problematic in the region of the target product. • Use similarity for fine-grained search. • Similarity is problematic when far from the target product. • Use diversity to speed-up the search. T C1 Q C2 C3

9. Final Remarks

10. Questions?