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Blai Bonet Bretto

 
 

Blai Bonet Bretto- Universidad Simón Bolívar

Blai Bonet is a professor in the computer science department at Universidad Simón Bolívar, Venezuela. He received a Ph.D. degree in computer science from the University of California, Los Angeles. His research interests are in the areas of automated planning, heuristic search, and knowledge representation.

Blai has received six best paper awards or honorable mentions, including the 2009 and 2014 ICAPS Influential Paper Awards for pioneering work on the heuristic search approach for domain-independent planning. He is a co-author (with Hector Geffner) of the book titled "A Concise Introduction to Models and Methods for Automated Planning."

Blai Bonet is an associate editor of Artificial Intelligence and the Journal of Artificial Intelligence Research. He served as conference co-chair of the 22nd International Conference on Automated Planning and Scheduling (ICAPS-12) and as program co-chair of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), and he is a member of the AAAI Executive Council (2015-2018) and the ICAPS Executive Council (2012-2018).

Research stay at UC3M: DEPARTMENT OF COMPUTING

Project:

During my stay at the Universidad Carlos III de Madrid, I will work with the members of the Planning and Learning Group (PLG), specially with Daniel Borrajo Millán and Carlos Linares López in the areas of automated planning and heuristic search. One main topic of research is the area of generalized planning which addresses the problem of computing a general policy for a given class of similar planning problems. This area has advanced significantly in recent years.

Another topic of research is the development of on-line algorithms for planning under non-determinism and partial observability. This type of planning provides models that are more expresive and relevant when addressing real-world problems than the models provided by classical planning. Both research topics involve expertise and knowledge from different areas such as planning, heuristic search and machine learning. I also look forward to participate in the current research projects pursued by the PLG.