Bahram Sadeghi Bigham

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For fast and efficient analysis of large sets of fuzzy data, elimination of redundancies in the memory representation is needed. We used MTBDDs as the underlying data-structure to represent fuzzy sets and binary fuzzy relations. This leads to elimination of redundancies in the representation, less computations, and faster analyses. We have also extended a(More)
This paper proposes a new learning-based behavior model for a soccer goalkeeper robot using Petri nets. The work aim at modeling and analyzing, both qualitatively and quantitatively, the goalkeeper role in order to have a model-based knowledge of the task performance in different possible situations. The different primitive actions and behaviors as well as(More)