Descriptive Complexity

By virtue of the close relationship between logic and relational databases, it turns out that complexity has important applications to databases such as analyzing the parallel time needed to compute a query, and the analysis of nondeterministic classes. This book is a relatively self-contained introduction to the subject, which includes the necessary background material, as well as numerous examples and exercises.

From the Preface: We hope that this small volume will suggest directions of synergy and contact for future researchers to build upon, creating connections and making discoveries that will help explain some of the many mysteries of computation. Finite model theory can be succinctly described as the study of logics on finite structures. It is an area of research existing between mathematical logic and computer science. This area has been developing through continuous interaction with computational complexity, database theory, and combinatorics. The volume presents articles by leading researchers who delivered talks at the "Workshop on Finite Models and Descriptive Complexity" at Princeton in January 1996 during a DIMACS sponsored Special Year on Logic and Algorithms. Each article is self-contained and provides a valuable introduction to the featured research areas connected with finite model theory. This text will also be of interest to those working in discrete mathematics and combinatorics.

This groundbreaking, yet accessible book explores the interaction between graph theory and computational complexity using methods from finite model theory.

Descriptive complexity theory establishes a connection between the computational complexity of algorithmic problems (the computational resources required to solve the problems) and their descriptive complexity (the language resources required to describe the problems). This groundbreaking book approaches descriptive complexity from the angle of modern structural graph theory, specifically graph minor theory. It develops a 'definable structure theory' concerned with the logical definability of graph theoretic concepts such as tree decompositions and embeddings. The first part starts with an introduction to the background, from logic, complexity, and graph theory, and develops the theory up to first applications in descriptive complexity theory and graph isomorphism testing. It may serve as the basis for a graduate-level course. The second part is more advanced and mainly devoted to the proof of a single, previously unpublished theorem: properties of graphs with excluded minors are decidable in polynomial time if, and only if, they are definable in fixed-point logic with counting.

This collection brings together the authors' previous research with new work on the Register-Functional (RF) approach to grammatical complexity, offering a unified theoretical account for its further study. The book traces the development of the RF approach from its foundations in two major research strands of linguistics: the study of sociolinguistic variation and the text-linguistic study of register variation. Building on this foundation, the authors demonstrate the RF framework at work across a series of corpus-based research studies focused specifically on grammatical complexity in English. The volume highlights early work exploring patterns of grammatical complexity in present-day spoken and written registers as well as subsequent studies which extend this research to historical patterns of register variation and the application of RF research to the study of writing development for L1 and L2 English university students. Taken together, along with the addition of introductory chapters connecting the different studies, the volume offers readers with a comprehensive resource to better understand the RF approach to grammatical complexity and its implications for future research. The volume will appeal to students and scholars with research interests in either descriptive linguistics or applied linguistics, especially those interested in grammatical complexity and empirical, corpus-based approaches.

The book is based on the PhD thesis “Descriptive Set Theoretic Methods in Automata Theory,” awarded the E.W. Beth Prize in 2015 for outstanding dissertations in the fields of logic, language, and information. The thesis reveals unexpected connections between advanced concepts in logic, descriptive set theory, topology, and automata theory and provides many deep insights into the interplay between these fields. It opens new perspectives on central problems in the theory of automata on infinite words and trees and offers very impressive advances in this theory from the point of view of topology. "...the thesis of Michał Skrzypczak offers certainly what we expect from excellent mathematics: new unexpected connections between a priori distinct concepts, and proofs involving enlightening ideas.” Thomas Colcombet.

"Small Dynamic Complexity Classes" was awarded the E.W. Beth Dissertation Prize 2016 for outstanding dissertations in the fields of logic, language, and information. The thesis studies the foundations of query re-evaluation after modifying a database. It explores the structure of small dynamic descriptive complexity classes and provides new methods for proving lower bounds in this dynamic context. One of the contributions to the former aspect helped to confirm the conjecture by Patnaik and Immerman (1997) that reachability can be maintained by first-order update formulas.

The classical theory of computation has its origins in the work of Goedel, Turing, Church, and Kleene and has been an extraordinarily successful framework for theoretical computer science. The thesis of this book, however, is that it provides an inadequate foundation for modern scientific computation where most of the algorithms are real number algorithms. The goal of this book is to develop a formal theory of computation which integrates major themes of the classical theory and which is more directly applicable to problems in mathematics, numerical analysis, and scientific computing. Along the way, the authors consider such fundamental problems as: * Is the Mandelbrot set decidable? * For simple quadratic maps, is the Julia set a halting set? * What is the real complexity of Newton's method? * Is there an algorithm for deciding the knapsack problem in a ploynomial number of steps? * Is the Hilbert Nullstellensatz intractable? * Is the problem of locating a real zero of a degree four polynomial intractable? * Is linear programming tractable over the reals? The book is divided into three parts: The first part provides an extensive introduction and then proves the fundamental NP-completeness theorems of Cook-Karp and their extensions to more general number fields as the real and complex numbers. The later parts of the book develop a formal theory of computation which integrates major themes of the classical theory and which is more directly applicable to problems in mathematics, numerical analysis, and scientific computing.

In Complexity and Postmodernism, Paul Cilliers explores the idea of complexity in the light of contemporary perspectives from philosophy and science. Cilliers offers us a unique approach to understanding complexity and computational theory by integrating postmodern theory (like that of Derrida and Lyotard) into his discussion. Complexity and Postmodernism is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.

This book explores the contributions, actual and potential, of complexity thinking to educational research and practice. While its focus is on the theoretical premises and the methodology, not specific applications, the aim is pragmatic--to present complexity thinking as an important and appropriate attitude for educators and educational researchers. Part I is concerned with global issues around complexity thinking, as read through an educational lens. Part II cites a diversity of practices and studies that are either explicitly informed by or that might be aligned with complexity research, and offers focused and practiced advice for structuring projects in ways that are consistent with complexity thinking. Complexity thinking offers a powerful alternative to the linear, reductionist approaches to inquiry that have dominated the sciences for hundreds of years and educational research for more than a century. It has captured the attention of many researchers whose studies reach across traditional disciplinary boundaries to investigate phenomena such as: How does the brain work? What is consciousness? What is intelligence? What is the role of emergent technologies in shaping personalities and possibilities? How do social collectives work? What is knowledge? Complexity research posits that a deep similarity among these phenomena is that each points toward some sort of system that learns. The authors’ intent is not to offer a complete account of the relevance of complexity thinking to education, not to prescribe and delimit, but to challenge readers to examine their own assumptions and theoretical commitments--whether anchored by commonsense, classical thought or any of the posts (such as postmodernism, poststructuralism, postcolonialism, postpositivism, postformalism, postepistemology) that mark the edges of current discursive possibility. Complexity and Education is THE introduction to the emerging field of complexity thinking for the education community. It is specifically relevant for educational researchers, graduate students, and inquiry-oriented teacher practitioners.