CORDIS Project
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This project develops an interpretable reinforcement learning method to uncover hidden physical laws in complex systems. By integrating projective simulation, graph neural networks, and variable disentanglement, it aims to enhance understanding in areas like condensed matter physics and robotics through interpretable m…
In recent years, the use of machine learning (ML) for the study of physics has experienced a strong boost.
However, most of the machines used are black boxes, and the causal relation between inputs and outputs is often impossible to extract.
Nonetheless, a critical aspect when dealing with physical systems is not only to make correct predictions, but to understand the physical laws which underlie these assessments.
Recently, an increasing number of works aim at developing interpretable ML method…
UNIVERSITAET INNSBRUCK
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