This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
|
teaching:mfe:ia [2015/04/11 17:47] stuetzle [Stochastic Local Search heuristics for solving NP-complete puzzles.] |
teaching:mfe:ia [2016/03/11 11:46] stuetzle [Optimising Ant Colony Algorithms for Performance] |
||
|---|---|---|---|
| Line 1: | Line 1: | ||
| - | ====== MFE 2013-2014 : Intelligence Artificielle ====== | + | ====== MFE 2015-2016 : Intelligence Artificielle ====== |
| ===== Introduction ===== | ===== Introduction ===== | ||
| Line 178: | Line 178: | ||
| * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| - | |||
| - | ===== Optimising Ant Colony Algorithms for Performance ====== | ||
| - | |||
| - | Ants have inspired a number of computational techniques and among the most successful is ant colony optimization (ACO). ACO is an optimization technique that can be applied to tackle a wide variety of computational problems that arise in computer science, telecommunications, and engineering. | ||
| - | |||
| - | The goal of this project is to improve the performance of ACO algorithms by investigating and testing various implementation techniques: intrinsic functions (MMX/SSE floating-point operations), CPU cache effects, or GPU programming. | ||
| - | |||
| - | Required skills: knowledge of C programming. Some knowledge about computer architecture. | ||
| - | |||
| - | * Contacts : | ||
| - | * [[http://iridia.ulb.ac.be/~mdorigo|Marco Dorigo (IRIDIA)]] | ||
| - | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| - | |||
| Line 229: | Line 216: | ||
| * 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)]] | ||