Toby Walsh - Böcker

Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics.The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area.The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming.- Covers the whole field of constraint programming- Survey-style chapters- Five chapters on applications

Can we build moral machines?Artificial intelligence is an essential part of our lives – for better or worse. It can be used to influence what we buy, who gets shortlisted for a job and even how we vote. Without AI, medical technology wouldn’t have come so far, we’d still be getting lost in our GPS-free cars, and smartphones wouldn’t be so, well, smart. But as we continue to build more intelligent and autonomous machines, what impact will this have on humanity and the planet?Professor Toby Walsh, a world-leading researcher in the field of artificial intelligence, explores the ethical considerations and unexpected consequences AI poses. Can AI be racist? Can robots have rights? What happens if a self-driving car kills someone? What limitations should we put on the use of facial recognition? Machines Behaving Badly is a thought-provoking look at the increasing human reliance on robotics and the decisions that need to be made now to ensure the future of AI is a force for good, not evil.

This book is devoted to recent progress made in solving propositional satisfiability and related problems. Propositional satisfiability is a powerful and general formalism used to solve a wide range of important problems including hardware and software verification. The core of many reasoning problems in automated deduction are propositional. Research into methods to automate such reasoning has therefore a long history in artificial intelligence. In 1957, Allen Newell and Herb Simon introduced the Logic Theory Machine to prove propositional theorems from Whitehead and Russel's "Principia mathematica".In 1960, Martin Davis and Hillary Putnam introduced their eponymous decision procedure for satisfiability reasoning (though, for space reasons, it was quickly superseded by the modified procedure proposed by Martin Davis, George Logemann and Donald Loveland two years later). In 1971, Stephen Cook's proof that propositional satisfiability is NP-Complete placed satisfiability as the cornerstone of complexity theory.

Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion.This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter.This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work.Edmund Clarke, 2007 ACM Turing Award Recipient: ""SAT solving is a key technology for 21st century computer science.""Donald Knuth, 1974 ACM Turing Award Recipient:""SAT is evidently a killer app, because it is key to the solution of so many other problems.""Stephen Cook, 1982 ACM Turing Award Recipient:""The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?""

‘Refreshingly clear-eyed … Faking It is an insightful and intelligent book that’s a must for those looking for facts about AI hype.’ – Books+Publishing‘AI will be as big a game-changer as the smart phone and the personal computer – or bigger! This book will help you navigate the revolution.’ – Dr Karl KruszelnickiArtificial intelligence is, as the name suggests, artificial and fundamentally different to human intelligence. Yet often the goal of AI is to fake human intelligence. This deceit has been there from the very beginning. We’ve been trying to fake it since Alan Turing answered the question ‘Can machines think?’ by proposing that machines pretend to be humans.Now we are starting to build AI that truly deceives us. Powerful AIs such as ChatGPT can convince us they are intelligent and blur the distinction between what is real and what is simulated. In reality, they lack true understanding, sentience and common sense. But this doesn’t mean they can’t change the world.Can AI systems ever be creative? Can they be moral? What can we do to ensure they are not harmful? In this fun and fascinating book, Professor Toby Walsh explores all the ways AI fakes it, and what this means for humanity – now and in the future.

Table of Contents: Introduction / Preference Modeling and Reasoning / Uncertainty in Preference Reasoning / Aggregating Preferences / Stable Marriage Problems

This book constitutes the thoroughly refereed conference proceedings of the 4th International Conference on Algorithmic Decision Theory , ADT 2015, held in September 2015 in Lexington, USA. The 32 full papers presented were carefully selected from 76 submissions. The papers are organized in topical sections such as preferences;

This book constitutes the refereed proceedings of the 20th International Conference on Theory and Applications of Satisfiability Testing, SAT 2017, held in Melbourne, Australia, in August/September 2017.The 22 revised full papers, 5 short papers, and 3 tool papers were carefully reviewed and selected from 64 submissions. The papers are organized in the following topical sections: algorithms, complexity, and lower bounds; clause learning and symmetry handling; maximum satisfiability and minimal correction sets; parallel SAT solving; quantified Boolean formulas; satisfiability modulo theories; and SAT encodings.

The 8th International Conference on Theory and Applications of Satis?ability Testing(SAT2005)providedaninternationalforumforthemostrecentresearch on the satis?ablity problem (SAT). SAT is the classic problem of determining whether or not a propositional formula has a satisfying truth assignment. It was the ?rst problem shown by Cook to be NP-complete. Despite its seemingly specialized nature, satis?ability testing has proved to extremely useful in a wide range of di?erent disciplines, both from a practical as well as from a theoretical point of view. For example, work on SAT continues to provide insight into various fundamental problems in computation, and SAT solving technology has advanced to the point where it has become the most e?ective way of solving a number of practical problems. The SAT series of conferences are multidisciplinary conferences intended to bring together researchers from various disciplines who are interested in SAT. Topics of interest include, but are not limited to: proof systems and proof c- plexity; search algorithms and heuristics; analysis of algorithms; theories beyond the propositional; hard instances and random formulae; problem encodings; - dustrial applications; solvers and other tools. This volume contains the papers accepted for presentation at SAT 2005. The conference attracted a record number of 73 submissions. Of these, 26 papers were accepted for presentation in the technical programme. In addition, 16 - pers were accepted as shorter papers and were presented as posters during the technicalprogramme.Theacceptedpapersandposterpaperscoverthefullrange of topics listed in the call for papers.

This book constitutes the refereed proceedings of the 7th International Conference on Principles and Practice of Constraint Programming, CP 2001, held in Paphos, Cyprus, in November/December 2001.The 37 revised full papers, 9 innovative applications presentations, and 14 short papers presented were carefully reviewed and selected from a total of 135 submissions. All current issues in constraint processing are addressed, ranging from theoretical and foundational issues to advanced and innovative applications in a variety of fields.

This book constitues the refereed proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation, SARA 2000, held at Lake LBJ, Texas, USA in July 2000. The nine revised full papers presented together with five extended abstracts, three posters, seven research summaries, and four invited papers were carefully reviewed and selected for inclusion in the book. The book addresses all current aspects of abstraction, reformulation, and approximation and applications in areas like automatic programming, constraint satisfaction, design, diagnosis, inductive logic programming, computational learning, planning, resource allocation, theorem proving, qualitative reasoning, relational databases, etc.

This book is devoted to recent progress made in solving propositional satisfiability and related problems. Propositional satisfiability is a powerful and general formalism used to solve a wide range of important problems including hardware and software verification. The core of many reasoning problems in automated deduction are propositional. Research into methods to automate such reasoning has therefore a long history in artificial intelligence. In 1957, Allen Newell and Herb Simon introduced the Logic Theory Machine to prove propositional theorems from Whitehead and Russel's "Principia mathematica".In 1960, Martin Davis and Hillary Putnam introduced their eponymous decision procedure for satisfiability reasoning (though, for space reasons, it was quickly superseded by the modified procedure proposed by Martin Davis, George Logemann and Donald Loveland two years later). In 1971, Stephen Cook's proof that propositional satisfiability is NP-Complete placed satisfiability as the cornerstone of complexity theory.