模型论逻辑与理论计算机科学

近年来，逻辑中语义的思想与方法在理论计算机科学的许多分支中的渗透与应用，已愈来愈受重视．作为语义方法的逻辑基础，（一阶）模型论是研究（一阶）逻辑的语法构造与语义属性之间联系的一门数理逻辑的分支；而模型论逻辑（又称广义模型论）则是在抽象逻辑的框架中，用模型论的方法研究各种扩充逻辑系统的异、同及相互关系．本文从抽象逻辑的观点出发．介绍模型论中与计算机科学（ＣＳ）密切相关的若干概念及其应用．特别是广义的有限模型论，它在ＣＳ的刺激下于８０年代形成并急速发展起来，已在数据库、计算复杂性以及形式语言与自动机等理论中取得突出成果或重大的应用．     

Extending possibilistic logic over Gödel logic

In this paper we present several fuzzy logics trying to capture different notions of necessity (in the sense of possibility theory) for Gödel logic formulas. Based on different characterizations of necessity measures on fuzzy sets, a group of logics with Kripke style semantics is built over a restricted language, namely, a two-level language composed of non-modal and modal formulas, the latter, moreover, not allowing for nested applications of the modal operator N. Completeness and some computational complexity results are shown.     

Computational adequacy for recursive types in models of intuitionistic set theory

This paper provides a unifying axiomatic account of the interpretation of recursive types that incorporates both domain-theoretic and realizability models as concrete instances. Our approach is to view such models as full subcategories of categorical models of intuitionistic set theory. It is shown that the existence of solutions to recursive domain equations depends upon the strength of the set theory. We observe that the internal set theory of an elementary topos is not strong enough to guarantee their existence. In contrast, as our first main result, we establish that solutions to recursive domain equations do exist when the category of sets is a model of full intuitionistic Zermelo–Fraenkel set theory. We then apply this result to obtain a denotational interpretation of FPC, a recursively typed lambda-calculus with call-by-value operational semantics. By exploiting the intuitionistic logic of the ambient model of intuitionistic set theory, we analyse the relationship between operational and denotational semantics. We first prove an “internal” computational adequacy theorem: the model always believes that the operational and denotational notions of termination agree. This allows us to identify, as our second main result, a necessary and sufficient condition for genuine “external” computational adequacy to hold, i.e. for the operational and denotational notions of termination to coincide in the real world. The condition is formulated as a simple property of the internal logic, related to the logical notion of 1-consistency. We provide useful sufficient conditions for establishing that the logical property holds in practice. Finally, we outline how the methods of the paper may be applied to concrete models of FPC. In doing so, we obtain computational adequacy results for an extensive range of realizability and domain-theoretic models.     

Tractability frontiers in probabilistic team semantics and existential second-order logic over the reals

Probabilistic team semantics is a framework for logical analysis of probabilistic dependencies. Our focus is on the axiomatizability, complexity, and expressivity of probabilistic inclusion logic and its extensions. We identify a natural fragment of existential second-order logic with additive real arithmetic that captures exactly the expressivity of probabilistic inclusion logic. We furthermore relate these formalisms to linear programming, and doing so obtain PTIME data complexity for the logics. Moreover, on finite structures, we show that the full existential second-order logic with additive real arithmetic can only express NP properties. Lastly, we present a sound and complete axiomatization for probabilistic inclusion logic at the atomic level.     

Strategies and simulations in a semantic framework

By means of several examples of structural operational semantics for a variety of languages, we justify the importance and interest of using the notions of strategies and simulations in the semantic framework provided by rewriting logic and implemented in the Maude metalanguage. On the one hand, we describe a basic strategy language for Maude and show its application to CCS, the ambient calculus, and the parallel functional language Eden. On the other hand, we show how the concept of stuttering simulation can be used inside Maude to show that a stack machine correctly implements the operational semantics of a simple functional language.     

Choice functions and well-orderings over the infinite binary tree

We give a new proof showing that it is not possible to define in monadic second-order logic (MSO) a choice function on the infinite binary tree. This result was first obtained by Gurevich and Shelah using set theoretical arguments. Our proof is much simpler and only uses basic tools from automata theory. We show how the result can be used to prove the inherent ambiguity of languages of infinite trees. In a second part we strengthen the result of the non-existence of an MSO-definable well-founded order on the infinite binary tree by showing that every infinite binary tree with a well-founded order has an undecidable MSO-theory.     

Generalized periodicity and primitivity for words

Starting from six kinds of periodicity of words we define six sets of words which are primitive in different senses and we investigate their relationships. We show that only three of the sets are external Marcus contextual languages with choice but none of them is an external contextual language without choice or an internal contextual language. For the time complexity of deciding any of our sets by one-tape Turing machines, n ² is a lower bound and this is optimal in two cases. The notions of roots and degrees of words and languages, which are strongly connected to periodicity and primitivity, are also considered, and we show that there can be an arbitrarily large gap between the complexity of a language and that of its roots. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Computational complexity of hybrid interval temporal logics

Interval logics are very expressive temporal formalisms, but reasoning with them is often undecidable or has high computational complexity. As a result, a vast number of approaches limiting their expressive power—in order to obtain better computational behaviour—have been introduced. Unfortunately, due to such restrictions, interval logics often lose referentiality, that is, the capacity to refer to specific time intervals, which is crucial for temporal representation and reasoning. The computational price that needs to be paid in order to regain referentiality is not well studied and our research aims to fill this gap. In particular we study the main interval temporal logic, called the Halpern-Shoham logic, and its low complexity modifications. To regain referentiality in these modifications, we extend the language with the hybrid machinery—nominals and satisfaction operators—and classify the obtained logics according to their computational complexity. We show that such a hybridisation often makes tractable logics intractable but not undecidable. This allows us to construct hybrid interval temporal logics which are referential as well as maintain a good compromise between expressiveness and complexity; it makes them valuable formalisms for temporal knowledge representation. We also introduce a class of models which, due to a specific interplay between the interpretation of modal operators and a structure of time, makes reasoning in interval logics computationally hard even in the absence of the hybrid machinery.     

Understanding by semantic language,operation logic and formularies

The aim of the paper is to supply tools for developing the proposed mathematical semantic theory of anthropoecosystems. The paper constructs the semantic language which is equivalent (according to transferring information) to any of natural languages. The operation logic is settled. Its well-defined formulas are semantic language formulas. Its reasoning is realized by production system blocks, each being the sequence of modus ponens rules. Operation logic represents a model how humans, maybe, realize information processing. It allows contradictions and can avoid the dimensionality deadlock. The universal program for answering questions is presented. The introduction to formulary theory is given by means of which the notion of the understanding of systems is formulated. It enables to understand and control very large systems by computer artificial intelligence on the basis of qualitative information and why-role how-roles pairs. In the paper the notions like humans, language, animals, understanding, consciousness, are simplified modelling notions which are only similar to the real existing ones.     

Logic and Natural Selection

Is logic, feasibly, a product of natural selection? In this paper we treat this question as dependent upon the prior question of where logic is founded. After excluding other possibilities, we conclude that logic resides in our language, in the shape of inferential rules governing the logical vocabulary of the language. This means that knowledge of (the laws of) logic is inseparable from the possession of the logical constants they govern. In this sense, logic may be seen as a product of natural selection: the emergence of logic requires the development of creatures who can wield structured languages of a specific complexity, and who are capable of putting the languages to use within specific discursive practices.     

On the fixed parameter complexity of graph enumeration problems definable in monadic second-order logic

We discuss the parametrized complexity of counting and evaluation problems on graphs where the range of counting is definable in monadic second-order logic (MSOL). We show that for bounded tree-width these problems are solvable in polynomial time. The same holds for bounded clique width in the cases, where the decomposition, which establishes the bound on the clique-width, can be computed in polynomial time and for problems expressible by monadic second-order formulas without edge set quantification. Such quantifications are allowed in the case of graphs with bounded tree-width. As applications we discuss in detail how this affects the parametrized complexity of the permanent and the hamiltonian of a matrix, and more generally, various generating functions of MSOL definable graph properties. Finally, our results are also applicable to SAT and ♯SAT.     

On the Presburger fragment of logics with multiteam semantics

In team semantics, which is the basis of modern logics of dependence and independence, formulae are evaluated on sets of assignments, called teams. Multiteam semantics instead takes mulitplicities of data into account and is based on multisets of assignments, called multiteams. Logics with multiteam semantics can be embedded into a two-sorted variant of existential second-order logics, with arithmetic operations on multiplicities. Here we study the Presburger fragment of such logics, permitting only addition, but not multiplication on multiplicities. It can be shown that this fragment corresponds to inclusion-exclusion logic in multiteam semantics, but, in contrast to the situation in team semantics, that it is strictly contained in independence logic. We give different characterisations of this fragment by various atomic dependency notions.     

Generalized derivatives and nonsmooth optimization, a finite dimensional tour

During the early 1960’s there was a growing realization that a large number of optimization problems which appeared in applications involved minimization of non-differentiable functions. One of the important areas where such problems appeared was optimal control. The subject of nonsmooth analysis arose out of the need to develop a theory to deal with the minimization of nonsmooth functions. The first impetus in this direction came with the publication of Rockafellar’s seminal work titledConvex Analysis which was published by the Princeton University Press in 1970. It would be impossible to overstate the impact of this book on the development of the theory and methods of optimization. It is also important to note that a large part of convex analysis was already developed by Werner Fenchel nearly twenty years earlier and was circulated through his mimeographed lecture notes titledConvex Cones, Sets and Functions, Princeton University, 1951. In this article we trace the dramatic development of nonsmooth analysis and its applications to optimization in finite dimensions. Beginning with the fundamentals of convex optimization we quickly move over to the path breaking work of Clarke which extends the domain of nonsmooth analysis from convex to locally Lipschitz functions. Clarke was the second doctoral student of R.T. Rockafellar. We discuss the notions of Clarke directional derivative and the Clarke generalized gradient and also the relevant calculus rules and applications to optimization. While discussing locally Lipschitz optimization we also try to blend in the computational aspects of the theory wherever possible. This is followed by a discussion of the geometry of sets with nonsmooth boundaries. The approach to develop the notion of the normal cone to an arbitrary set is sequential in nature. This approach does not rely on the standard techniques of convex analysis. The move away from convexity was pioneered by Mordukhovich and later culminated in the monographVariational Analysis by Rockafellar and Wets. The approach of Mordukhovich relied on a nonconvex separation principle called theextremal principle while that of Rockafellar and Wets relied on various convergence notions developed to suit the needs of optimization. We then move on to a parallel development in nonsmooth optimization due to Demyanov and Rubinov called Quasidifferentiable optimization. They study the class of directionally differentiable functions whose directional derivatives can be represented as a difference of two sublinear functions. On other hand the directional derivative of a convex function and also the Clarke directional derivatives are sublinear functions of the directions. Thus it was thought that the most useful generalizations of directional derivatives must be a sublinear function of the directions. Thus Demyanov and Rubinov made a major conceptual change in nonsmooth optimization. In this section we define the notion of a quasidifferential which is a pair of convex compact sets. We study some calculus rules and their applications to optimality conditions. We also study the interesting notion of Demyanov difference between two sets and their applications to optimization. In the last section of this paper we study some second-order tools used in nonsmooth analysis and try to see their relevance in optimization. In fact it is important to note that unlike the classical case, the second-order theory of nonsmoothness is quite complicated in the sense that there are many approaches to it. However we have chosen to describe those approaches which can be developed from the first order nonsmooth tools discussed here. We shall present three different approaches, highlight the second order calculus rules and their applications to optimization.     

Heuristics and look-ahead integration to solve constraint satisfaction problems efficiently

Logic programming languages, such asProlog, allow a declarative specification of Constraint Satisfaction Problems (CSPs), freeing the user from specifying more or less complex control directives. However, the price to pay for such flexibility is a loss of efficiency, which makes Logic Programming inadequate to solve CSPs of even moderate size and complexity. To extend the range of applicability of logic programming, several improvements have been proposed. The use of heuristics is one such improvement. Although this usually forces the user to specify some form of control (thus abandoning the pure declarative nature of a logic program), these specifications can be made declarative by making use of some appropriate meta-predicates. Another extension to logic programming that improves its efficiency, is the active use of constraints, as done in the various formulations of constraint logic programming languages. In particular, the use of finite domains is quite adequate to implement look-ahead schemes to efficiently solve several types of CSPs. In this paper, we discuss the complementary nature of heuristics and look-ahead schemes and present a constraint logic programming framework that integrates both these techniques. Results obtained with a time-tabling problem executed on a prototype that implements such a framework are presented, and show that significant efficiency improvements can be achieved when compared with the separate use of the two techniques.     

Abstract Logics, Logic Maps, and Logic Homomorphisms

What is a logic? Which properties are preserved by maps between logics? What is the right notion for equivalence of logics? In order to give satisfactory answers we generalize and further develop the topological approach of [4] and present the foundations of a general theory of abstract logics which is based on the abstract concept of a theory. Each abstract logic determines a topology on the set of theories. We develop a theory of logic maps and show in what way they induce (continuous, open) functions on the corresponding topological spaces. We also establish connections to well-known notions such as translations of logics and the satisfaction axiom of institutions [5]. Logic homomorphisms are maps that behave in some sense like continuous functions and preserve more topological structure than logic maps in general. We introduce the notion of a logic isomorphism as a (not necessarily bijective) function on the sets of formulas that induces a homeomorphism between the respective topological spaces and gives rise to an equivalence relation on abstract logics. Therefore, we propose logic isomorphisms as an adequate and precise notion for equivalence of logics. Finally, we compare this concept with another recent proposal presented in [2]. This research was supported by the grant CNPq/FAPESB 350092/2006-0.     

Effectiveness in RPL, with applications to continuous logic

In this paper, we introduce a foundation for computable model theory of rational Pavelka logic (an extension of ?ukasiewicz logic) and continuous logic, and prove effective versions of some related theorems in model theory. We show how to reduce continuous logic to rational Pavelka logic. We also define notions of computability and decidability of a model for logics with computable, but uncountable, set of truth values; we show that provability degree of a formula with respect to a linear theory is computable, and use this to carry out an effective Henkin construction. Therefore, for any effectively given consistent linear theory in continuous logic, we effectively produce its decidable model. This is the best possible, since we show that the computable model theory of continuous logic is an extension of computable model theory of classical logic. We conclude with noting that the unique separable model of a separably categorical and computably axiomatizable theory (such as that of a probability space or an L^p Banach lattice) is decidable.     

A quantitative nonlinear strong ergodic theorem for Hilbert spaces

We give a quantitative version of a strong nonlinear ergodic theorem for (a class of possibly even discontinuous) selfmappings of an arbitrary subset of a Hilbert space due to R. Wittmann and outline how the existence of uniform bounds in such quantitative formulations of ergodic theorems can be proved by means of a general logical metatheorem. In particular these bounds depend neither on the operator nor on the initial point. Furthermore, we extract such uniform bounds in our quantitative formulation of Wittmann?s theorem, implicitly using the proof-theoretic techniques on which the metatheorem is based. However, we present our result and its proof in analytic terms without any reference to logic as such. Our bounds turn out to involve nested iterations of relatively low computational complexity. While in theory these kind of iterations ought to be expected, so far this seems to be the first occurrence of such a nested use observed in practice.     

Approximation to measurable functions and its relation to probabilistic computation

A theory of approximation to measurable sets and measurable functions based on the concepts of recursion theory and discrete complexity theory is developed. The approximation method uses a model of oracle Turing machines, and so the computational complexity may be defined in a natural way. This complexity measure may be viewed as a formulation of the average-case complexity of real functions—in contrast to the more restrictive worst-case complexity. The relationship between these two complexity measures is further studied and compared with the notion of the distribution-free probabilistic computation. The computational complexity of the Lebesgue integral of polynomial-time approximable functions is studied and related to the question “FP = ♯P?”.