Equipe MaLis : MAchine Learning and Interactive Systems



Research Topics

The problem we are dealing with is to extract meaningful information from heterogeneous data (digital or symbolic) and to build models able to reproduce (simulation), classify (detection, pattern recognition) or control (automation, robotics, human-computer interfaces) the behaviour of the systems having generated the observed information. The ultimate aim of the MaLIS research group is to build situated systems, able to behave optimally in their environment and interact with it using their perceptions. The integration of perception (sensing), action (behaviour) and reasoning in a single process is know as the situated perception paradigm.

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