Computational aspects of the active self

80
Nicht eingeplant
20m
Von-Melle-Park 4

Von-Melle-Park 4

Poster

Beschreibung

We, as humans, routinely talk about ourselves, but what is this “self”, how does it arise, and what influences it? What are the underlying mechanisms that help humans perceive themselves and act in the world? Recent work studies the so-called minimal self and shows how the sense of body-ownership, agency and control contribute to it. In our research, as part of the DFG SPP “the active self”, we investigate the minimal self and its emergence through sensorimotor experiences of embodied agents by utilizing information theory and reinforcement learning. Focusing on artificial agents enables us to extensively experiment and analyze their internal representations to further understand the minimal self.

Keywords

minimal self
reinforcement learning
information theory
embodied intelligence
machine learning

Autoren

Frank Röder (Institute for Data Science Foundations - Hamburg University of Technology) Carlotta Langer (Institute for Data Science Foundations - Hamburg University of Technology)

Co-Autoren

Jan Dohmen (Institute for Data Science Foundations - Hamburg University of Technology) Dr. Manfred Eppe (Institute for Data Science Foundations - Hamburg University of Technology) Prof. Nihat Ay (Institute for Data Science Foundations - Hamburg University of Technology)

Präsentationsmaterialien