Mathematics

This book provides an introduction to, and analysis of, the use of Bayesian nets in causal modelling. It puts forward new conceptual foundations for causal network modelling: The book argues that probability and causality need to be interpreted as epistemic notions in order for the key assumptions behind causal models to hold. Under the epistemic view, probability and causality are understood in terms of the beliefs an agent ought to adopt. The book develops an objective Bayesian notion of probability and a corresponding epistemic theory of causality. This yields a general framework for causal modelling, which is extended to cope with recursive causal relations, logically complex beliefs and changes in an agent's language.

There is a need for integrated thinking about causality, probability, and mechanism in scientific methodology. A panoply of disciplines, ranging from epidemiology and biology through to econometrics and physics, routinely make use of these concepts to infer causal relationships. But each of these disciplines has developed its own methods, where causality and probability often seem to have different understandings, and where the mechanisms involved often look very different. This variegated situation raises the question of whether progress in understanding the tools of causal inference in some sciences can lead to progress in other sciences, or whether the sciences are really using different concepts. Causality and probability are long-established central concepts in the sciences, with a corresponding philosophical literature examining their problems. The philosophical literature examining the concept of mechanism, on the other hand, is more recent and there has been no clear account of how mechanisms relate to causality and probability. If we are to understand causal inference in the sciences, we need to develop some account of the relationship between causality, probability, and mechanism. This book represents a joint project by philosophers and scientists to tackle this question, and related issues, as they arise in a wide variety of disciplines across the sciences.

The complexity and the randomness aspect of a set of natural numbers are closely related. Traditionally, computability theory is concerned with the complexity aspect. However, computability theoretic tools can also be used to introduce mathematical counterparts for the intuitive notion of randomness of a set. Recent research shows that, conversely, concepts and methods originating from randomness enrich computability theory. The book is about these two aspects of sets of natural numbers and about their interplay. For the first aspect, lowness and highness properties of sets are introduced. For the second aspect, firstly randomness of finite objects are studied, and then randomness of sets of natural numbers. A hierarchy of mathematical randomness notions is established. Each notion matches the intuition idea of randomness to some extent. The advantages and drawbacks of notions weaker and stronger than Martin-Löf randomness are discussed. The main topic is the interplay of the computability and randomness aspects. Research on this interplay has advanced rapidly in recent years. One chapter focuses on injury-free solutions to Post's problem. A core chapter contains a comprehensible treatment of lowness properties below the halting problem, and how they relate to K triviality. Each chapter exposes how the complexity properties are related to randomness. The book also contains analogs in the area of higher computability theory of results from the preceding chapters, reflecting very recent research.

Constructive mathematics is a vital area of research which has gained special attention in recent years due to the distinctive presence of computational content in its theorems. This characteristic had been already stressed by Bishop in his fundamental contribution to the subject, Foundations of Constructive Analysis (1967). Following Bishop's new approach to mathematics based on intuitionistic logic, various formal systems were introduced in the early 1970s with the intent to clarify the notion of set theory underlying his work. This book addresses the relationship between foundations and practice of constructive mathematics Bishop-style, by presenting on the one hand some very recent contributions to constructive analysis and formal topology, and on the other hand studies which underline the capabilities and expressiveness of various formal systems which have been introduced as foundations for constructive mathematics, like constructive set and type theories. The book aims to provide a point of reference by pesenting up-to-date contributions by some of the most active scholars in each field. A variety of approaches and techniques are represented to give as wide a view as possible and promote cross-fertilization between different styles and traditions. The book also aims at further promoting awareness and discussion on the issue of bridging foundations and practice of constructive mathematics, thus filling the apparent distance that has emerged between them in recent years.

Bayesian epistemology aims to answer the following question: How strongly should an agent believe the various propositions expressible in her language? Subjective Bayesians hold that.it is largely (though not entirely) up to the agent as to which degrees of belief to adopt. Objective Bayesians, on the other hand, maintain that appropriate degrees of belief are largely (though not entirely) determined by the agent's evidence. This book states and defends a version of objective Bayesian epistemology. According to this version, objective Bayesianism is characterized by three norms: (i) Probability: degrees of belief should be probabilities; (ii) Calibration: they should be calibrated with evidence; and (iii) Equivocation: they should otherwise equivocate between basic outcomes. Objective Bayesianism has been challenged on a number of different fronts: for example, it has been accused of being poorly motivated, of failing to handle qualitative evidence, of yielding counter‐intuitive degrees of belief after updating, of suffering from a failure to learn from experience, of being computationally intractable, of being susceptible to paradox, of being language dependent, and of not being objective enough. The book argues that these criticisms can be met and that objective Bayesianism is a promising theory with an exciting agenda for further research.

This book focuses on interpolation and definability. This notion is not only central in pure logic, but has significant meaning and applicability in all areas where logic itself is applied, especially in computer science, artificial intelligence, logic programming, philosophy of science, and natural language. The book provides basic knowledge on interpolation and definability in logic, and contains a systematic account of material which has been presented in many papers. A variety of methods and results are presented beginning with the famous Beth's and Craig's theorems in classical predicate logic (1953-57), and to the most valuable achievements in non-classical topics on logic, mainly intuitionistic and modal logic. Together with semantical and proof-theoretic methods, close interrelations between logic and universal algebra are established and exploited.

This a research study about logic. Logic is both part of and has roles in many disciplines, including inter alia, mathematics, computing, and philosophy. The topic covered here — the mathematical theory of reductive logic and proof-search — draws upon the techniques and cultures of all three disciplines, but is mainly about mathematics and computation. Since its earliest presentations, mathematical logic has been formulated as a formalization of deductive reasoning: given a collection of hypotheses, a conclusion is derived. However, the advent of computational logic has emphasized the significance of reductive reasoning: given a putative conclusion, what are sufficient premises? Whilst deductive systems typically have a well-developed semantics of proofs, reductive systems are typically well-understood only operationally. Typically, a deductive system can be read as a corresponding reductive system. The process of calculating a proof of a given putative conclusion, for which non-deterministic choices between premises must be resolved, is called proof-search and is an essential enabling technology throughout the computational sciences. This study suggests that the reductive view of logic is as fundamental as the deductive view, and discusses some of the problems that must be addressed in order to provide a semantics of proof-searches of comparable value to the corresponding semantics of proofs. Just as the semantics of proofs is intimately related to the model theory of the underlying logic, so too should be the semantics of reductions and of proof-search. The study discusses how to solve the problem of providing a semantics for proof-searches in intuitionistic logic, which adequately models both not only the logical but also via an embedding of intuitionistic reductive logic into classical reductive logic, the operational aspects, i.e., control of proof-search, of the reductive system. It concludes with a naturally motivated example of our semantics of proof-search: a class of games.

This is the third edition of a well-known graduate textbook on Boolean-valued models of set theory. The aim of the first and second editions was to provide a systematic and adequately motivated exposition of the theory of Boolean-valued models as developed by Scott and Solovay in the 1960s, deriving along the way the central set theoretic independence proofs of Cohen and others in the particularly elegant form that the Boolean-valued approach enables them to assume. In this edition, the background material has been augmented to include an introduction to Heyting algebras. It includes chapters on Boolean-valued analysis and Heyting-algebra-valued models of intuitionistic set theory.

This book gives an account of the present state of research on lattices of elementary substructures and automorphisms of nonstandard models of arithmetic. Major representation theorems are proved, and the important particular case of countable recursively saturated models is discussed in detail. All necessary technical tools are developed. The list includes: constructions of elementary simple extensions; a partial classification of arithmetic types, in particular Gaifman's theory of definable types; forcing in arithmetic; elements of the Kirby-Paris combinatorial theory of cuts; Lascar's generic automorphisms; and applications of Abramson and Harrington's generalization of Ramsey's theorem. There are also chapters discussing ω₁-like models with interesting second order properties, and a chapter on order types of nonstandard models.