Hugues Juillé

• I used to be a member of the research lab for the study of Dynamical & Evolutionary Machine Organization, based in the Computer Science Department , Volen National Center for Complex Systems at Brandeis University, MA 02254-9110, USA.
  



• I completed my Ph.D. thesis in May 1999. My thesis advisor was Prof. Jordan Pollack .
  My dissertation was titled: Methods for Statistical Inference: Extending the Evolutionary Computation Paradigm .
  


• From September 1998 to August 1999, I was working in Research and Development at the Cambridge office of i2 Technologies . I was working on the development of GA-based optimisation algorithms for scheduling.
  


• In September 1999, I moved to Paris, France. Since then, I have been working at eurobios .
  You can e-mail me there at Hugues.Juille@eurobios.com .

The rules of the game: learn everything, read everything, inquire into everything... When two texts, or two assertions, or perhaps two ideas, are in contradiction, be ready to reconcile them rather than cancel one by the other; regard them as two different facets, or two successive stages, of the same reality, a reality convincingly human just because it is complex.
                        - Marguerite Yourcenar

Research Interests

• Massively parallel search algorithms
• Fine-grained models for AI
• Genetic Algorithms, Evolutionary Computation, Genetic Programming
• Neural networks
• Optimization techniques
• Machine learning

About my recent work

• Sorting networks and the END search algorithm
• Coevolving Intertwined Spirals
• I am also applying some of my algorithms to solve problems from the Abbadingo challenge. Now, the competition is over and I ended up as one of the two winners!
• Coevolving the "Ideal" Trainer: I am very interested in the study of coevolutionary approaches for learning. My recent work resulted in the discovery of new rules for 1-dimensional CA that significantly outperform the previously known rules to implement a particular classification task (the majority function).

Personal Information