This master thesis describes an intelligent classifier system applied to multiclass non-linearly separable problems called Slicer. The system adopts a low computacional cost supervised learning strategy (evaluated as ) ...

Development in robotics has advanced over the past few decades, this way, robots are increasingly present both in people’s daily lives, with models for locomotion, fun, and in the industry for improving working conditions, ...

This work describes a new classification technique called P2C - Partitioning to Classify. The main goal is to achieve reasonable classification performances using linear prediction methods, even on datasets with non-linear ...

This dissertation deals with the problem of scheduling single machine with earliness and tardiness penalties, with sequence dependent setup and due windows.For contextualization of the problem studied, some techniques used ...