Prabhas Chongstitvatana
This talk introduces Coincidence Algorithm which is designed for
combinatorial optimization. Coincidence Algorithm (COIN) belongs to the
class of Estimation of Distribution Algorithm. The algorithms in this
class use probabilistic models to solve hard problems. They are
considered to be the modern successor of Genetic Algorithms. The
emphasise in this talk is on the use of negative examples in Coincidence
Algorithm. Learning from negative examples helps the algorithm to avoid
repeating the mistakes that had already been found.
I will give background about Coincidence Algorithm including its working
mechanism. Then I will report the recent result from my research team.
The strength of COIN in solving multimodal puzzles will be demonstrated.
The analysis on the behavior of the algorithm based on what it learn from
negative examples is presented. Some applications in industrial
engineering field will be highlighted.
Prabhas Chongstitvatana earned B.Eng. in Electrical Engineering from
Kasetsart University, Thailand in 1980 and Ph.D. from the department of
artificial intelligence, Edinburgh University, U.K. in 1992. Presently,
he is a professor in the department of computer engineering, Chulalongkorn
University. His research includes robotics, evolutionary computation and
computer architecture. He is actively promote the collaboration to create
Thai national grid for scientific computing. He is the lifetime member of
Thailand Engineering Institute, Thai Academy of Science and Technology,
Thai Robotics Society, Thai Embedded System Association and IEEE Robotics
and Automation Society. Presently he is the president of ECTI Association
of Thailand. He has been awarded National Distinguished Researcher, from
National Research Council, Thailand in 2009.