Knauer, KoljaVentosa Andreu, Laura2023-06-192023-06-192023-01-23https://hdl.handle.net/2445/199425Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2023, Director: Kolja Knauer[en] This thesis explores the great potential of computer-assisted proofs in the advancement of mathematical knowledge, with a special focus on using computers to refute conjectures by finding counterexamples, sometimes a humanly impossible task. In recent years, mathematicians have become more aware that machine learning techniques can be extremely helpful for finding counterexamples to conjectures in a more efficient way than by using exhaustive search methods. In this thesis we do not only present the theoretical background behind some of these methods but also implement them to try to refute some graph theory conjectures.62 p.application/pdfengcc-by-nc-nd (c) Laura Ventosa Andreu, 2023codi: GPL (c) Laura Ventosa Andreu, 2023http://creativecommons.org/licenses/by-nc-nd/3.0/es/http://www.gnu.org/licenses/gpl-3.0.ca.htmlTeoria de grafsTreballs de fi de grauSistemes adaptatiusProgramació (Matemàtica)Aprenentatge automàticDemostració automàtica de teoremesGraph theoryBachelor's thesesAdaptive control systemsMathematical programmingMachine learningAutomatic theorem provinginfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/openAccess