1. Evolving service logic using natural selection Peter Martin
Service Creation using Genetic Programming
Evolving service logic using natural selection Peter Martin
© 1999 Marconi Communications Limited. All Rights Reserved.

2. Genetic Programming Evolving computer programs Natural selection
Fitness improves survival
Genetic inheritance

3. Steps in Using GP Start Create Population Test for Fitness No
End of
Run ?
Evolve Next
Generation No

4. Creating a population Select suitable functions and data
Functional considerations - Sufficiency
Problem Specific!
Syntactical considerations - Closure
All programs must be legal!
Example:- Division by zero!
Randomly create programs
Population size ?
Program size ?

5. Testing for Fitness The Fitness function Execution or Interpretation
Fitness is problem specific
Each individual is given a score

6. Evolving Generations Select fittest individuals
Fitness proportionate or
Tournament selection
Use the fittest to create next generation
Reproduction operators
Mutation
Asexual reproduction (copy)
Sexual Reproduction (crossover)

7. Crossover Individual A Individual C Individual B Individual D F1 F2 T1re 6 T4 F3 T5 T6
Individual A
Individual B
Parents
Crossover
point
Crossover point A 2 1 B
Offspring F3 T5 T6 F1 T1
Individual C A 1 B 2 F2 T2 T3 T4
Individual D A 2

8. Evolving Generations Start Create Population Test for Fitness
Evolve Next
Generation No
End of Run
Yes
End

9. An Example - Service Creation
Number Translation
Translate number depending on time of day
Fitness derived from Message Sequence

10. Call Sequence for a Service
Switch
DataBase
Logic
IDP (CalledDN) DB
Request(
CalledDN << 1)
DBResp
(TAD1) DB
Request(TAD1 << 1)
DBResp
(TAD2)
Connect(TAD2 << 1)
End

11. The Function Set for Services
Building block operations
START
Database lookup
ROUTE
String manipulation
END

12. Data Types for Services
Telephony services require many data types
Telephone numbers
Integers
Boolean
Polymorphic data representation
Any variable is composed of sub-variables
Each variable has one of each type of sub-variable
All programs are legal!

13. Example Service Logic

14. The Outcome Service Logic creation successful
Great variety of programs
Fitness represents testing
Fitness is the specification
Software Engineering Management issues
Specification vs. Coding
Other Issues?
Any hidden surprises?

15. Conclusions GP shown to be a powerful technique Novel programs evolved
Step towards automatic program generation
Shifts focus from HOW to WHAT