1. Case Based Reasoning Lecture 1: Introduction Professor Susan Craw
B18a (via secretary)
Lecture/Lab Notes available on the Virtual Campus and

2. Outline The Limitations of Rules Solving Problems Case Based Reasoning
Applications
Reading

3. The Limitations of Rules
The success of rule-based expert systems is due to several factors:
They can mimic some human problem-solving strategies
Rules are a part of everyday life, so people can relate to them
However, a significant limitation is the knowledge elicitation bottleneck
Experts may be unable to articulate their expertise
Heuristic knowledge is particularly difficult
Experts may be too busy…

4. Another Way We Solve Problems?
By remembering how we solved a similar problem in the past
This is Case Based Reasoning (CBR)
memory-based problem-solving
re-using past experiences
Experts often find it easier to relate stories about past cases than to formulate rules

5. Elephants Never Forget!
Some biologists suggest that elephants’ success in harsh environments may be due to their memories.
A herd of elephants retains a collective memory of problems and their solutions:
E.g., they remember where water can usually be found during a drought.
Elephants can solve problems without using models or rules.

6. Databases
Database technology would seem ideally suited to the task of retrieving known solutions to problems
Databases are excellent at finding exact matches…
But are poor at near or fuzzy matches
I’ve got the Answer  What’s the Question?

7. The CBR Cycle Solution Review Retain Adapt Database Retrieve Similar
New
Problem

8. R4 Cycle
Retrieve the cases from the case-base whose problem is most similar to the new problem.
Reuse the solutions from the retrieved cases to create a proposed solution for the new problem.
Revise the proposed solution to take account of the problem differences between the new problem and the problems in the retrieved cases.
Retain the new problem and its revised solution as a new case for the case-base if appropriate.

9. Definitions of CBR
Case-based reasoning is […] reasoning by remembering
A case-based reasoner solves new problems by adapting solutions that were used to solve old problems
Case-based reasoning is a recent approach to problem solving and learning […]
Leake, 1996
Riesbeck & Schank, 1989
Aamodt & Plaza, 1994

10. CBR Assumption(s) The main assumption is that: Two other assumptions:
Similar problems have similar solutions:
e.g., an aspirin can be taken for any mild pain
Two other assumptions:
The world is a regular place: what holds true today will probably hold true tomorrow
(e.g., if you have a headache, you take aspirin, because it has always helped)
Situations repeat: if they do not, there is no point in remembering them
(e.g., it helps to remember how you found a parking space near that restaurant)

11. Problems We Solve This Way
Medicine
doctor remembers previous patients, especially for rare combinations of symptoms
Law
English/US law depends on precedence
case histories are consulted
Management
decisions are often based on past rulings
Financial
performance is predicted by past results

12. Good / Bad Applications for CBR
Classification tasks (good for CBR)
Diagnosis - what type of fault is this?
Prediction / estimation - what happened when we saw this pattern before?
Synthesis tasks (harder for CBR)
Engineering Design
Planning
Scheduling

13. Success Stories for CBR
Failure prediction
ultrasonic NDT of rails for Dutch railways
water in oil wells for Schlumberger
Failure analysis
Mercedes cars for DaimlerChrysler
semiconductors at National Semiconductor
Maintenance scheduling
Boeing 737 engines
TGV trains for SNCF
Planning
mission planning for US navy
route planning for DaimlerChrysler cars

14. Success Stories for CBR
e-Commerce
sales support for standard products
sales support for customised products
Personalisation
TV listings from Changing Worlds
music on demand from Kirch Media
news stories via car radios for DaimlerBenz
Re-Design
gas taps for Copreci
Formulation (recipes)
rubber for racing tyres for Pirelli
colouring plastics for General Electric
tablets for AstraZeneca

15. Impact on Business @ Microsoft
Within 9 months of introducing a CBR Microsoft’s call centre in Glasgow
Microsoft reported:
10% increase in customer satisfaction rating
28% increase in “first-time-fix” success rate
13% increase in the “agent is informed” customer survey score
A significant reduction in the time required to train new agents
More consistent responses delivered by agents, regardless of the problem

16. CBR Honours Project Ideas
CBR for filtering (anti-SPAM)
Michael Long, BSc(Hons) 2004, SPAM filtering
Amandine Orecchioni, 2005, Management
CBR for Diagnosis
Katya Ponce do Leon, MSc 2005, Fish Diagnosis for Marine Lab
Grant Gauld, BSc(Hons) 2005, CBR Helpdesk for Chevron-Texaco
CBR for Planning
Abhishek Chakraborty, MSc 2005, CBR Healthcare Planning for Partners Research Emergency Nutrition
Scott Morrice, BSc(Hons) 2004, “Killer Bunnies” game
If you are interested in a CBR project next year
see me or Nirmalie Wiratunga

17. Reading Article Books www.aaai.org/Library/Magazine/Vol26/vol26.html
Tenth anniversary of the plastics color formulation tool, William Cheetham, AI Magazine, Vol 26, Fall, 2005.
Books
I. Watson. Applying Knowledge Management: Techniques For Building Corporate Memories. Morgan Kaufmann, 2003.
I. Watson. Applying Case-Based Reasoning: Techniques for Enterprise Systems. Morgan Kaufmann, 1997.

18. CBR Resources CBR on the web CBR Commercial Solutions
CBR Commercial Solutions
Orenge from
Kaidara Adviser from (
eGain (
Customer Service & Contact Centre Software
CBR Tools in our School
CBR-Works from
ReCall from
Weka from