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Workshop

Reinforcement Learning and Computer Algebra

  • Dylan Peifer (Cornell University, Ithaca, NY, USA)
E1 05 (Leibniz-Saal)
Attention: this event is cancelled.

Abstract

Performing Buchberger's algorithm, the standard algorithm for computing Groebner bases, involves making many important choices. In particular, the strategy for selecting the next s-pair to process can make dramatic differences in the time and space needed for the computation. While we have several heuristics for pair selection, reinforcement learning provides tools for exploring and developing new strategies for both Buchberger's algorithm and other algorithms in computer algebra.

Attention: this event is cancelled.

Attention: this event is cancelled.

Saskia Gutzschebauch

Max-Planck-Institut für Mathematik in den Naturwissenschaften Contact via Mail

Heather Harrington

University of Oxford

Eliana Duarte Gelvez

Max Planck Institute for Mathematics in the Sciences

Thomas Kahle

Otto-von-Guericke-Universität