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teaching:mfe:ia [2015/04/11 17:39]
stuetzle [Feature Extraction and Automatic Algorithm Selection.]
teaching:mfe:ia [2015/04/11 17:50]
stuetzle [Feature Extraction and Automatic Algorithm Selection.]
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     * [[http://​iridia.ulb.ac.be/​~lperez|Leslie Perez (IRIDIA)]]     * [[http://​iridia.ulb.ac.be/​~lperez|Leslie Perez (IRIDIA)]]
  
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-===== Stochastic Local Search heuristics for solving NP-complete puzzles. ====== 
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-This project is about single player games (puzzles) and the design of algorithms for tackling hard combinatorial optimisation problems. ​ 
-Example puzzles are: [[http://​en.wikipedia.org/​wiki/​Light_Up|Light Up]], [[http://​en.wikipedia.org/​wiki/​Mastermind_(board_game)|Mastermind]],​ [[http://​en.wikipedia.org/​wiki/​Minesweeper_(video_game)|Minesweeper]],​ etc. 
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-The student will learn how to design and implement a Stochastic Local Search algorithm to solve NP-complete puzzles. The student will also learn how to analyse the performaces of the algorithm and perform statistically sound comparisons with the other algorithms available in literature. 
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-Required skills: good knowledge of C or C++ programming. ​ 
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-  * Contacts :  
-    * [[http://​iridia.ulb.ac.be/​~stuetzle|Thomas Stützle (IRIDIA)]] ​ 
-    * [[http://​iridia.ulb.ac.be/​~fmascia|Franco Mascia (IRIDIA)]] ​   
  
  
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   * Contacts :    * Contacts : 
     * [[http://​iridia.ulb.ac.be/​~stuetzle|Thomas Stützle (IRIDIA)]] ​     * [[http://​iridia.ulb.ac.be/​~stuetzle|Thomas Stützle (IRIDIA)]] ​
 +    * [[http://​code.ulb.ac.be/​iridia.people.php?​id=1393|Alberto Franzin (IRIDIA)]] ​
  
  
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-===== Applications of the Multi-objective ACO framework =====+===== Applications of a hybrid SLS algorithm ​framework =====
  
-We have recently developed a software framework ​of Ant Colony Optimization ​algorithms ​for multi-objective optimization problems. This framework has only been applied to a few problems. The goal of this project would be to extend this framework to other problems and compare its results with the methods proposed in the literature. The student will learn to solve multi-objective ​optimization problems with ACO algorithms, automatic configuration of optimization algorithms, and analysis and comparison of optimization algorithms ​for multi-objective problems.+We have recently developed a software framework ​from which hybrid stochastic local search ​algorithms ​can be designed automatically. This framework has only been applied to a few problems. The goal of this project would be to extend this framework to other problems and compare its results with the methods proposed in the literature. The student will learn to solve combinatorial ​optimization problems with SLS algorithms, automatic configuration of optimization algorithms, and analysis and comparison of optimization algorithms.
  
   * Contacts :    * Contacts : 
-    * [[http://​iridia.ulb.ac.be/​~manuel|Manuel López-Ibáñez (IRIDIA)]] 
     * [[http://​iridia.ulb.ac.be/​~stuetzle|Thomas Stützle (IRIDIA)]] ​     * [[http://​iridia.ulb.ac.be/​~stuetzle|Thomas Stützle (IRIDIA)]] ​
-    * [[http://iridia.ulb.ac.be/~mdorigo|Marco Dorigo ​(IRIDIA)]] ​+    * [[http://code.ulb.ac.be/iridia.people.php?​id=1388|Federico Pagnozzi ​(IRIDIA)]]
  
  
  
-===== Automatic fine-tuning of an evolutionary multi-objective framework ===== 
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-The goal of this project is to explore the possibilities of using automatic configuration tools for fine-tuning an existing [[http://​paradiseo.gforge.inria.fr/​index.php?​n=Paradiseo.MOEO|evolutionary multi-objective framework]]. The student will learn about automatic configuration tools, evolutionary algorithms for multi-objective optimization problems and analysis and comparison of multi-objective algorithms. 
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-  * Contacts :  
-    * [[http://​iridia.ulb.ac.be/​~manuel|Manuel López-Ibáñez (IRIDIA)]] 
-    * [[http://​iridia.ulb.ac.be/​~stuetzle|Thomas Stützle (IRIDIA)]] ​ 
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teaching/mfe/ia.txt · Last modified: 2024/07/01 16:15 by stuetzle