loading subjects...
Ebook: Advanced Tools and Methods for Treewidth-Based Problem Solving
loading...
This book, Advanced Tools and Methods for Treewidth-Based Problem Solving, contains selected results from the author’s PhD studies, which were carried out from 2015 to 2021. For his PhD thesis, Markus Hecher received the EurAI Dissertation Award 2021 and the GI Dissertation Award 2021, amongst others.
The aim of the book is to present a new toolkit for using the structural parameter of treewidth to solve problems in knowledge representation and reasoning (KR) and artificial intelligence (AI), thereby establishing both theoretical upper and lower bounds, as well as methods to deal with treewidth efficiently in practice. The key foundations outlined in the book provide runtime lower bounds – under reasonable assumptions in computational complexity – for evaluating quantified Boolean formulas and logic programs which match the known upper bounds already published in 2004 and 2009.
The general nature of the developed tools and techniques means that a wide applicability beyond the selected problems and formalisms tackled in the book is anticipated, and it is hoped that the book will serve as a starting point for future theoretical and practical investigations, which will no doubt establish further results and gain deeper insights.
This book contains selected results of my PhD studies, carried out according to an individual binational agreement between TU Wien (Austria) and the university of Potsdam (Germany), from 2015 to 2021. Originally, it appeared as my PhD thesis, for which I was awarded with the EurAI Dissertation Award 2021 (See: https://www.eurai.org/award/markus-hecher). As a result, this book is published in the series Frontiers in Artificial Intelligence and Applications – Dissertations in Artificial Intelligence (FAIA-DAIS) by IOS Press; see [Hecher, 2022] for an extended abstract.
The overall goal of this book is to present a new toolkit on using the structural parameter treewidth for problems in knowledge representation and reasoning (KR) and artificial intelligence (AI), thereby establishing both theoretical upper and lower bounds, as well as methods to efficiently deal with treewidth in practice. Key foundations of this work provide runtime lower bounds for evaluating Quantified Boolean formulas (and logic programs), which — under reasonable assumptions in computational complexity — match known upper bounds that were published back in 2004 (and 2009). By the general nature of the developed tools and techniques, we expect a wide applicability beyond the selected problems and formalisms tackled in this book. We hope that this book will serve as a starting point in establishing further results and gaining deeper insights that foster future theoretical and practical investigations. For current follow-up works and up-to-date research, I refer to my website at TU Wien (See: https://dbai.tuwien.ac.at/staff/hecher).
I am very grateful for everybody, who supported this work. More detailed acknowledgements are below.
August 2022
Markus Hecher