Evolutionary Algorithms Guilherme Oliveira What is
Description: Evolutionary Algorithms Guilherme Oliveira What is it about ? Population based optimization algorithms Reproduction Mutation Recombination Selection Example of what it can do Goal is to minimize Schwefels function Example of what it can do
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slide1. Evolutionary Algorithms Guilherme Oliveira<br>
slide2. What is it about ? Population based optimization algorithms
Reproduction
Mutation
Recombination
Selection<br>
slide3. Example of what it can do Goal is to minimize Schwefel’s function<br>
slide4. Example of what it can do<br>
slide5. How ?<br>
slide6. Inner topics Genetic Algorithm
Genetic Programming
Evolutionary Programming
Gene Expression Programming
Evolution Strategy
Differential Evolution
And more<br>
slide7. How is it related to AI ? Broad state space
Decision making<br>
slide8. Project Progress Studies
EA
biology
Writing almost done
Discussion about EA
Discussion about biology
Relation between them
Related work
Came up with my own opinion, about to be concluded<br>
slide9. Difficulties of the project Extensive topic
Complex codes in prolog
Complex math relation<br>
slide10. What I’ve learned EA
Different approach to solve generic problems
New technique to find approximated solutions
Knowledge about the existence of algorithms to solve real problems that simulates life’s behavior<br>
slide11. Final Consideration I expect to finish my work on time<br>
slide12. Presentations images & information sources http://en.wikipedia.org/wiki/Evolutionary_algorithm#Evolutionary_algorithm_type
http://msdn.microsoft.com/en-us/magazine/jj133825.aspx
http://physiol.gu.se/maberg/figures/EAalgorithmPedagogical.png<br>
slide2. What is it about ? Population based optimization algorithms
Reproduction
Mutation
Recombination
Selection<br>
slide3. Example of what it can do Goal is to minimize Schwefel’s function<br>
slide4. Example of what it can do<br>
slide5. How ?<br>
slide6. Inner topics Genetic Algorithm
Genetic Programming
Evolutionary Programming
Gene Expression Programming
Evolution Strategy
Differential Evolution
And more<br>
slide7. How is it related to AI ? Broad state space
Decision making<br>
slide8. Project Progress Studies
EA
biology
Writing almost done
Discussion about EA
Discussion about biology
Relation between them
Related work
Came up with my own opinion, about to be concluded<br>
slide9. Difficulties of the project Extensive topic
Complex codes in prolog
Complex math relation<br>
slide10. What I’ve learned EA
Different approach to solve generic problems
New technique to find approximated solutions
Knowledge about the existence of algorithms to solve real problems that simulates life’s behavior<br>
slide11. Final Consideration I expect to finish my work on time<br>
slide12. Presentations images & information sources http://en.wikipedia.org/wiki/Evolutionary_algorithm#Evolutionary_algorithm_type
http://msdn.microsoft.com/en-us/magazine/jj133825.aspx
http://physiol.gu.se/maberg/figures/EAalgorithmPedagogical.png<br>