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.     

CTL AgentSpeak(L): A specification language for agent programs

This work introduces CTL AgentSpeak(L), a logic to specify and verify expected properties of rational agents implemented in the well-known agent oriented programming language AgentSpeak(L). Our approach is closely related to the BDICTL multi-modal logic, used to reason about agents in terms of their beliefs (B), desires (D), intentions (I), and the temporal logic CTL. A new interpretation for the temporal operators, grounded in the transition system induced by the operational semantics of AgentSpeak(L), is proposed. The main contribution of the approach is a better understanding of the relation between the programming language and its logical specification, enabling us to prove expected or desired properties for any agent programmed in the language, e.g., commitment strategies. The results, as well as the specification language proposed, are very useful to reconcile computational and philosophical aspects of practical reasoning, e.g., approaching single-minded commitment as a policy-based reconsideration case.     

Theory of T-norms and fuzzy inference methods

In this paper, the theory of T-norm and T-conorm is reviewed and the T-norm, T-conorm and negation function are defined as a set of T-operators. Some typical T-operators and their mathematical properties are presented. Finally, the T-operators are extended to the conventional fuzzy reasoning methods which are based on the and operators. This extended fuzzy reasoning provides both a general and a flexible method for the design of fuzzy logic controllers and, more generally, for the modelling of any decision-making process.     

深入研究模糊逻辑的必要性与紧迫性

因为"取大取小"不是数学计算,所以基于"取大取小"的模糊逻辑不能为数值转换提供算法支撑,使得模糊理论面临无合适模型可用的被动境地.指出,模糊逻辑是逻辑的一个新的近似推理研究方向,它的量化方法是数值计算;目的是支撑隶属度转换,使得由指标隶属度确定的目标隶属度是"真值"在当前条件下的最优近似.模糊逻辑是在隶属度转换条件下对人类近似推理本领规范的一种方法.而进行规范的依据是区分权滤波的冗余理论,实质性计算是由冗余理论导出的、实现隶属度转换的非线性去冗算法;相应的隶属度转换模型是非线性数学模型.     

数理逻辑中的数值化方法

数理逻辑的本质是形式推理而不是数值计算,非此即彼式的严谨性是其特征,因而在一定意义下它是"两极化"的.比如,(1)一个逻辑理论或者是相容的,或者是不相容的,不存在"半相容的"理论.(2)"逻辑公式A是假设集T的推论"或者成立,或者不成立,说它近似成立是无意义的.(3)逻辑公式中有重言式和矛盾式,但没有0.8重言式.本文的目的在于为上述基本概念提供程度化的版本,并从而建立一种近似推理理论.     

Generalized resolution and cutting planes

This paper illustrates how the application of integer programming to logic can reveal parallels between logic and mathematics and lead to new algorithms for inference in knowledge-based systems. If logical clauses (stating that at least one of a set of literals is true) are written as inequalities, then the resolvent of two clauses corresponds to a certain cutting plane in integer programming. By properly enlarging the class of cutting planes to cover clauses that state that at least a specified number of literals are true, we obtain a generalization of resolution that involves both cancellation-type and circulant-type sums. We show its completeness by proving that it generates all prime implications, generalizing an early result by Quine. This leads to a cutting-plane algorithm as well as a generalized resolution algorithm for checking whether a set of propositions, perhaps representing a knowledge base, logically implies a given proposition. The paper is intended to be readable by persons with either an operations research or an artificial intelligence background.This report was prepared as part of the activities of the Management Sciences Research Group, Carnegie-Mellon University. Reproduction in whole or in part is permitted for any purpose of the U.S. Government.     

Logical form,mathematical practice,and Frege's Begriffsschrift

For over a century we have been reading Frege's Begriffsschrift notation as a variant of standard notation. But Frege's notation can also be read differently, in a way enabling us to understand how reasoning in Begriffsschrift is at once continuous with and a significant advance beyond earlier mathematical practices of reasoning within systems of signs. It is this second reading that I outline here, beginning with two preliminary claims. First, I show that one does not reason in specially devised systems of signs of mathematics as one reasons in natural language; the signs are not abbreviations of words. Then I argue that even given a system of signs within which to reason in mathematics, there are two ways one can read expressions involving those signs, either mathematically or mechanically. These two lessons are then applied to a reading of Frege's proof of Theorem 133 in Part III of his 1879 logic, a proof that Frege claims is at once strictly deductive and ampliative, a real extension of our knowledge. In closing, I clarify what this might mean, and how it might be possible.     

Fuzzy inequational logic

We present a logic for reasoning about graded inequalities which generalizes the ordinary inequational logic used in universal algebra. The logic deals with atomic predicate formulas of the form of inequalities between terms and formalizes their semantic entailment and provability in graded setting which allows to draw partially true conclusions from partially true assumptions. We follow the Pavelka approach and define general degrees of semantic entailment and provability using complete residuated lattices as structures of truth degrees. We prove the logic is Pavelka-style complete. Furthermore, we present a logic for reasoning about graded if–then rules which is obtained as particular case of the general result.     

An epistemic model of an agent who does not reflect on reasoning processes

This paper introduces an epistemic model of a boundedly rational agent under the two assumptions that (i) the agent’s reasoning process is in accordance with the model but (ii) the agent does not reflect on these reasoning processes. For such a concept of bounded rationality a semantic interpretation by the possible world semantics of the Kripke (1963) type is no longer available because the definition of knowledge in these possible world semantics implies that the agent knows all valid statements of the model. The key to my alternative semantic approach is the extension of the method of truth tables, first introduced for the propositional logic by Wittgenstein (1922), to an epistemic logic so that I can determine the truth value of epistemic statements for all relevant truth conditions. In my syntactic approach I define an epistemic logic–consisting of the classical calculus of propositional logic plus two knowledge axioms–that does not include the inference rule of necessitation, which claims that an agent knows all theorems of the logic. As my main formal result I derive a determination theorem linking my semantic with my syntactic approach. The difference between my approach and existing knowledge models is illustrated in a game-theoretic application concerning the epistemic justification of iterative solution concepts.     

Logical omniscience as infeasibility

Logical theories for representing knowledge are often plagued by the so-called Logical Omniscience Problem. The problem stems from the clash between the desire to model rational agents, which should be capable of simple logical inferences, and the fact that any logical inference, however complex, almost inevitably consists of inference steps that are simple enough. This contradiction points to the fruitlessness of trying to solve the Logical Omniscience Problem qualitatively if the rationality of agents is to be maintained. We provide a quantitative solution to the problem compatible with the two important facets of the reasoning agent: rationality and resource boundedness. More precisely, we provide a test for the logical omniscience problem in a given formal theory of knowledge. The quantitative measures we use are inspired by the complexity theory. We illustrate our framework with a number of examples ranging from the traditional implicit representation of knowledge in modal logic to the language of justification logic, which is capable of spelling out the internal inference process. We use these examples to divide representations of knowledge into logically omniscient and not logically omniscient, thus trying to determine how much information about the reasoning process needs to be present in a theory to avoid logical omniscience.     

L-fuzzy群理论的数理逻辑基础

Zadeh在文[1]中引入Fuzzy集概念之后，这一概念被Goguen[2]推广，真值域由单位闭区间被更一般的格所代替。Rosenfeld[3]将Zadeh的思想引入到群论中，提出Fuzzy群概念，真值域为格的Fuzzy群被称为L—fuzzy群[4]。本文的目的是用数理逻辑的语言陈述L—fuzzy群理论，构造L—fuzzy群的形式数学系统，从而建立L—fuzzy群理论的数理逻辑基础。     

Fuzzy sets in approximate reasoning,Part 1: Inference with possibility distributions

A survey of about twenty years of approximate reasoning based on fuzzy logic and possibility theory is proposed. It is not only made as an annotated bibliography of past works. It also emphasizes simple basic ideas that govern most of the existing methods, especially the principle of minimum specificify and the combination/projection principle that facilitate a comparison between fuzzy set-based methods and other numerical approaches to automated reasoning. Also, a significant part of the text is devoted to the representation of truth-qualified, certainty-qualified and possibility-qualified fuzzy statements. A new attempt to classify the numerous models of fuzzy “if … then” rules from a semantic point of view is presented. In the past, people have classified them according to algebraic properties of the underlying implication, or by putting constraints on the expected behavior of the inference process (by analogy with classical logic), or by running extensive comparative trials of particular implications on test-examples. Here the classification is based on whether the rules qualify the truth, the certainty or the possibility of their conclusions. Each case corresponds to a specific way of deriving the underlying conditional possibility distribution. This paper focuses on semantic approaches to approximate reasoning based on fuzzy sets, commonly exemplified by the generalized modus ponens, but also considers applications to current topics in Artificial Intelligence such as default reasoning and qualitative process modeling. A companion survey paper is devoted to syntax-oriented methods.     

Language technologies for semantic markup in mathematics

The Web Advanced Learning Technologies project showed how, by applying state of the art language technologies to semantic markup of mathematics, it is possible to automatically produce renderings of mathematical content in a variety of languages. The intended application area of this work is that of computer assisted assessment and testing in mathematics where standardized entry examinations for perspective students could be used independently of country and language. A similar multilingual approach can be developed for any situation in which it is possible to identify a specific mathematical jargon. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

基于三角范数的模糊逻辑中的三Ⅰ方法

三I推理方法是一种新的模糊推理方法,通过已有的研究成果表明,在许多方面它优于传统的CRI推理方法,它将成为模糊系统和人工智能的理论和应用研究中一个比较理想的推理机制。最近,国外学者提出了一个新的模糊逻辑形式系统,叫做Monoidal t-norm based logics(简记为MTL),已经证明这个形式系统是所有基于左连续三角范数的模糊逻辑的共同形式化。本文基于这类逻辑将三I推理方法形式化,从而在这些逻辑系统中为三推理方法找到了可靠的逻辑依据。     

An epistemic model of an agent who does not reflect on reasoning processes

This paper introduces an epistemic model of a boundedly rational agent under the two assumptions that (i) the agent’s reasoning process is in accordance with the model but (ii) the agent does not reflect on these reasoning processes. For such a concept of bounded rationality a semantic interpretation by the possible world semantics of the Kripke (1963) type is no longer available because the definition of knowledge in these possible world semantics implies that the agent knows all valid statements of the model. The key to my alternative semantic approach is the extension of the method of truth tables, first introduced for the propositional logic by Wittgenstein (1922), to an epistemic logic so that I can determine the truth value of epistemic statements for all relevant truth conditions. In my syntactic approach I define an epistemic logic–consisting of the classical calculus of propositional logic plus two knowledge axioms–that does not include the inference rule of necessitation, which claims that an agent knows all theorems of the logic. As my main formal result I derive a determination theorem linking my semantic with my syntactic approach. The difference between my approach and existing knowledge models is illustrated in a game-theoretic application concerning the epistemic justification of iterative solution concepts.     

Piaget's Logic of Meanings: Still Relevant Today

In his last book, Toward a Logic of Meanings ( Piaget & Garcia, 1991 ), Jean Piaget describes how thought can be categorized into a form of propositional logic, a logic of meanings. The intent of this article is to offer this analysis by Piaget as a means to understand the language and teaching of science. Using binary propositions, conjunctions, and disjunctions, a table of binary operations is used to analyze the structure of statements about conclusions drawn from observations of science phenomena. Two examples from science content illustrate how the logic of binary propositions is used to symbolize typical reasoning of secondary‐school science students. The content areas are the period of a pendulum and the Archimedes' Principle, which were chosen based on observations in secondary science classrooms. The analyses of the student responses in these two observations demonstrate the commonalities of arguments used by students of science as they try to make sense of observations. The analysis of students' reasoning, demonstrates that Piaget's logic of meanings is a useful and relevant tool for science educators' understanding of the syntactical aspects of pedagogical content knowledge.     

A simple logic for reasoning about incomplete knowledge

The semantics of modal logics for reasoning about belief or knowledge is often described in terms of accessibility relations, which is too expressive to account for mere epistemic states of an agent. This paper proposes a simple logic whose atoms express epistemic attitudes about formulae expressed in another basic propositional language, and that allows for conjunctions, disjunctions and negations of belief or knowledge statements. It allows an agent to reason about what is known about the beliefs held by another agent. This simple epistemic logic borrows its syntax and axioms from the modal logic KD. It uses only a fragment of the S5 language, which makes it a two-tiered propositional logic rather than as an extension thereof. Its semantics is given in terms of epistemic states understood as subsets of mutually exclusive propositional interpretations. Our approach offers a logical grounding to uncertainty theories like possibility theory and belief functions. In fact, we define the most basic logic for possibility theory as shown by a completeness proof that does not rely on accessibility relations.     

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．     

Inquisitive logic as an epistemic logic of knowing how

In this paper, we present an alternative interpretation of propositional inquisitive logic as an epistemic logic of knowing how. In our setting, an inquisitive logic formula α being supported by a state is formalized as knowing how to resolve α (more colloquially, knowing how α is true) holds on the S5 epistemic model corresponding to the state. Based on this epistemic interpretation, we use a dynamic epistemic logic with both know-how and know-that operators to capture the epistemic information behind the innocent-looking connectives in inquisitive logic. We show that the set of valid know-how formulas corresponds precisely to the inquisitive logic. The main result is a complete axiomatization with intuitive axioms using the full dynamic epistemic language. Moreover, we show that the know-how operator and the dynamic operator can both be eliminated without changing the expressivity over models, which is consistent with the modal translation of inquisitive logic existing in the literature. We hope our framework can give an intuitive alternative interpretation to various concepts and technical results in inquisitive logic, and also provide a powerful and flexible tool to handle both the inquisitive reasoning and declarative reasoning in an epistemic context.