ai-lect12

# ai-lect12 - This time Fuzzy Logic and Fuzzy Inference Why...

This preview shows pages 1–10. Sign up to view the full content.

1 This time: Fuzzy Logic and Fuzzy Inference Why use fuzzy logic? Tipping example Fuzzy set theory Fuzzy inference

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2 What is fuzzy logic? A super set of Boolean logic Builds upon fuzzy set theory Graded truth.  Truth values between True and False.  Not  everything is  either/or, true/false, black/white, on/off  etc. Grades of membership.  Class of tall men, class of far cities, class  of expensive things, etc. Lotfi Zadeh , UC/Berkely 1965.  Introduced  FL to model  uncertainty in natural language .    Tall, far, nice, large, hot, … Reasoning using linguistic terms .  Natural to express expert  knowledge.  If the weather is  cold  then wear  warm  clothing
3 Why use fuzzy logic? Pros: Conceptually easy to understand w/ “natural” maths Tolerant of imprecise data Universal approximation: can model arbitrary nonlinear functions Intuitive Based on linguistic terms Convenient  way to express expert and common sense knowledge Cons: Not a cure-all Crisp/precise models can be more efficient and even convenient Other approaches might be formally verified to work

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
4 Tipping example The Basic Tipping Problem:  Given a number between 0 and 10  that represents the quality of service at a restaurant what should the  tip be? Cultural footnote: An average tip for a meal in the U.S. is 15%,  which may vary depending on the quality of the service provided.
5 Tipping example: The non-fuzzy approach Tip = 15% of total bill What about quality of service?

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
6 Tipping example: The non-fuzzy approach Tip = linearly proportional to service from 5% to 25% tip = 0.20/10*service+0.05 What about quality of the food?
7 Tipping example: Extended The Extended Tipping Problem:  Given a number between 0 and  10 that represents the quality of service and the quality of the food at a restaurant, what should the tip be? How will this affect our tipping formula?

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
8 Tipping example: The non-fuzzy approach Tip = 0.20/20*(service+food)+0.05 We want service to be more important than food quality.  E.g., 80% for  service and 20% for food.
9 Tipping example: The non-fuzzy approach Tip =  servRatio*(.2/10*(service)+.05) + servRatio = 80%

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

## This note was uploaded on 01/20/2011 for the course CS 6810 taught by Professor Hecker during the Spring '10 term at CSU East Bay.

### Page1 / 37

ai-lect12 - This time Fuzzy Logic and Fuzzy Inference Why...

This preview shows document pages 1 - 10. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online