Agent的意图模型

意图是Agent的一个不可缺少的意识属性,在决定理性Agent的行为时起着重要的作用.已经有了若干种基于正规模态逻辑的意图模型,但它们存在着严重的“逻辑全知”问题.该文阐明意图不是正规模态算子,并提出了另一种意图模型,它不存在“逻辑全知”问题和其他相关问题(例如,副作用问题等).这种意图模型与Konolige和Pollack的意图模型相比,比较简单、自然,且满足K公理和联合一致性原理,实际上,为非正规模态算子基于正规可能世界的语义表示提供了一种新的方法.     

AN EPISTEMIC LOGIC WITH QUANTIFICATION OVER NAMES

Sentential theories of belief hold that propositions (the things that agents believe and know) are sentences of a representation language. To analyze quantification into the scope of attitudes, these theories require a naming map a function that maps objects to their names in the representation language. Epistemic logics based on sentential theories usually assume a single naming map, which is built into the logic. I argue that to describe everyday knowledge, the user of the logic must be able to define new naming maps for particular problems. Since the range of a naming map is usually an infinite set of names, defining a map requires quantification over names. This paper describes an epistemic logic with quantification over names, presents a theorem-proving algorithm based on translation to first-order logic, and proves soundness and completeness. The first version of the logic suffers from the problem of logical omniscience; a second version avoids this problem, and soundness and completeness are proved for this version also.     

Epistemic logic and logical omniscience: A survey

This survey brings together a collection of epistemic logics and discusses their approaches in alleviating the logical omniscience problem. Of particular note is the logic of implicit and explicit belief. Explicit belief refers to information actively held by an agent, while implicit belief refers to the logical consequence of explicit belief. Ramifications of Levesque's logic include nonstandard epistemic logic and the logics of awareness and local reasoning. Models of nonstandard epistemic logic are defined with respect to nonstandard proportional logic to weaken its semantics. In the logic of awareness, an agent can only believe a concept that it is aware of. Closely related to awareness are S-1 and S-3 epistemic operators which can be used to model skeptical and credulous agents. The logic of local reasoning provides a semantics for representing the fact that agents can have different clusters of beliefs which may contradict each other. Other variations include epistemic structures which are generalizations of the logic of local reasoning and fusion epistemic models which provide an account that agents can combine information conjunctively or disjunctively. Another closely related approach is the logic of explicit propostions which captures the insight that agents can hold beliefs independently without putting them together. © 1997 John Wiley & Sons, Inc.     

Logical omniscience, semantics, and models of belief

Logical omniscience may be described (roughly) as the state of affairs in which an agent explicitly believes anything which is logically entailed by that agent's beliefs. It is widely agreed that humans are not logically omniscient, and that an adequate formal model of belief, coupled with a correct semantic theory, would not entail logical omniscience. Recently, two prominent models of belief have emerged which purport both to avoid logical omniscience and to provide an intuitively appealing semantics. The first of these models is due to Levesque (1984 b ); the second to Fagin and Halpem (1985). It is argued herein that each of these models faces serious difficulties. Detailed criticisms are presented for each model, and a computationally oriented theory of intensions is presented which provides the foundation for a new formal model of belief. This formal model is presented in a decidable subset of first-order logic and is shown to provide a solution to the general problem of logical omniscience. The model provides for the possibility of belief revision and places no a priori restrictions upon an agent's representation language.     

Knowledge-Driven versus Data-Driven Logics

The starting point of this work is the gap between two distinct traditions in information engineering: knowledge representation and data-driven modelling. The first tradition emphasizes logic as a tool for representing beliefs held by an agent. The second tradition claims that the main source of knowledge is made of observed data, and generally does not use logic as a modelling tool. However, the emergence of fuzzy logic has blurred the boundaries between these two traditions by putting forward fuzzy rules as a Janus-faced tool that may represent knowledge, as well as approximate non-linear functions representing data. This paper lays bare logical foundations of data-driven reasoning whereby a set of formulas is understood as a set of observed facts rather than a set of beliefs. Several representation frameworks are considered from this point of view: classical logic, possibility theory, belief functions, epistemic logic, fuzzy rule-based systems. Mamdani's fuzzy rules are recovered as belonging to the data-driven view. In possibility theory a third set-function, different from possibility and necessity plays a key role in the data-driven view, and corresponds to a particular modality in epistemic logic. A bi-modal logic system is presented which handles both beliefs and observations, and for which a completeness theorem is given. Lastly, our results may shed new light in deontic logic and allow for a distinction between explicit and implicit permission that standard deontic modal logics do not often emphasize.     

智能规划的逻辑编码方式研究

逻辑编码方式的设计和实现是基于转换的规划方法有效处理的关键.对几种智能规划方法中的逻辑编码方式予以分析,分别介绍线性编码、基于Graphplan的编码、基于状态的编码、基于动作的编码、基于命题的编码、基于转移的编码、提升的因果编码、基于多值变元的编码、基于有向二元决策图的编码以及基于约束可满足的编码等,并结合国际规划竞赛和相关论文等的实验结论,说明上述编码方式的有效性和可行性,分析该类编码方式在其他领域的应用前景.最后,提出目前智能规划方法中逻辑编码方式研究所面临的挑战、可能的处理方法,以及与之相关的研究热点与趋势.     

Probabilistic Dynamic Epistemic Logic

In this paper I combine the dynamic epistemic logic ofGerbrandy (1999) with the probabilistic logic of Fagin and Halpern (1994). The resultis a new probabilistic dynamic epistemic logic, a logic for reasoning aboutprobability, information, and information change that takes higher orderinformation into account. Probabilistic epistemic models are defined, and away to build them for applications is given. Semantics and a proof systemis presented and a number of examples are discussed, including the MontyHall Dilemma.     

Updating Epistemic Logic Programs

We consider the problem of updating non-monotonic knowledgebases represented by epistemic logic programs where disjunctiveinformation and notions of knowledge and belief can be explicitlyexpressed. We propose a formulation for epistemic logic programupdate based on a principle called minimal change and maximalcoherence. The central feature of our approach is that duringan update or a sequence of updates, contradictory informationis removed on a basis of minimal change under the semanticsof epistemic logic programs and then coherent information ismaximally retained in the update result. Through various updatescenarios, we show that our approach provides both semanticand syntactic characterizations for an update problem. We alsoinvestigate essential semantic properties of epistemic logicprogram update.     

Temporal Properties of Repetitive Entities

Temporal entities are assertions (e.g. events, states) whose truth can be associated with time. An interesting problem in temporal reasoning is the problem of representing the fact that such entities are repeated over time. The problem has attracted some interest lately in the knowledge representation community. In this paper, we take a novel approach to the problem, which allows us to recognize repeated (or recurrent) entities as a class of temporal entities with well-defined properties. We derive some general properties for this important class of temporal entities, and some properties for an interesting subclass, namely the class of repetition of concatenable entities. Conacatenable entities have been called unrepeatable in the literature. As such we take a special interest in investigating their properties. The logical theory used here is a reified theory, which admits entity types, into its ontology as opposed to tokens, and uses Allens interval logic. Finally, we relate the new class of repetitive entities to existing classes in Shohams taxonomy.     

智能主体的信念认知时态子结构逻辑模型*

智能主体获取信念的途径主要有两种：一种为他省,通过外界交互,从其他主体获取信息;另一种为自省,通过自己的历史数据库获取相关知识。对于主体信念的描述与刻画,两种途径缺一不可,但当前的BDI理论模型中较多地为他省系统,没有做到两者相结合。其次,在当前的许多理论模型中,通常使用的是二值逻辑、经典模态逻辑或其变形系统,使得相应的逻辑系统普遍存在逻辑全知和粗精度刻画等问题。针对上述问题进行了相关研究,采用了认知时态子结构逻辑建模的方法,表达了智能主体获得“双省”信念的方式,针对其建立了相应的逻辑系统BSoET。     

The Dynamics of Syntactic Knowledge

The syntactic approach to epistemic logic avoids the logicalomniscience problem by taking knowledge as primary rather thanas defined in terms of possible worlds. In this study, we combinethe syntactic approach with modal logic, using transition systemsto model reasoning. We use two syntactic epistemic modalities:‘knowing at least’ a set of formulae and ‘knowingat most’ a set of formulae. We are particularly interestedin models restricting the set of formulae known by an agentat a point in time to be finite. The resulting systems are investigatedfrom the point of view of axiomatization and complexity. Weshow how these logics can be used to formalise non-omniscientagents who know some inference rules, and study their relationshipto other systems of syntactic epistemic logics, such as Ågotnesand Walicki (2004, Proc. 2nd EUMAS, pp. 1–10), Alechinaet al. (2004, Proc. 3rd AAMAS, pp. 601–613), Duc (1997,J. Logic Comput., 7, 633–648).     

Dealing with logical omniscience: Expressiveness and pragmatics

We examine four approaches for dealing with the logical omniscience problem and their potential applicability: the syntactic approach, awareness, algorithmic knowledge, and impossible possible worlds. Although in some settings these approaches are equi-expressive and can capture all epistemic states, in other settings of interest (especially with probability in the picture), we show that they are not equi-expressive. We then consider the pragmatics of dealing with logical omniscience—how to choose an approach and construct an appropriate model.     

认知描述逻辑ALCKR＋：描述逻辑的一个非单调扩展

描述逻辑是语义Web的逻辑基础,是形式化表达领域知识的工具.但是描述逻辑只能表达单调推理,不能处理不完全知识.认知描述逻辑因其非单调特性和良好的时间复杂度等特点在处理不完全知识方面有较好的优势.本文在认知描述逻辑ALCK的基础上提出了新的认知描述逻辑语言ALCKR ,保留了描述逻辑原有的优点,加入传递角色属性,增强了表达能力,并通过认知查询拥有了非单调推理的能力.设计了ALCKR 的语法、语义以及表算法.     

Nominal comparatives and Generalized Quantifiers

This work adopts the perspective of plural logic and measurement theory in order first to focus on the microstructure of comparative determiners; and second, to derive the properties of comparative determiners as these are studied in Generalized Quantifier Theory, locus of the most sophisticated semantic analysis of natural language determiners. The work here appears to be the first to examine comparatives within plural logic, a step which appears necessary, but which also harbors specific analytical problems examined here.Since nominal comparatives involve plural and mass reference, we begin with a domain of discourse upon which a lattice structure (Link's) is imposed, and which maps (via abstract dimensions such asweight in kilograms) to concrete measures (in N,R+). The mapping must be homomorphic and Archimedean. Comparisons begin as simple predicates on dimensions or measures; from these we derive classes of predicates on the domain, i.e., generalized determiners (quantifiers), and show, e.g., how monotonicity properties follow in the derivation. This results in a proposal for a logical language which includes derived determiners, and which is an attractive target for semantics interpretation; it also turns out that some interesting comparative determiners are first order, at least when restricted to nonparametric and noncollective predications.     

An Interpretation of Default Logic in Minimal Temporal Epistemic Logic

When reasoning about complex domains, where information available is usually only partial, nonmonotonic reasoning can be an important tool. One of the formalisms introduced in this area is Reiter's Default Logic (1980). A characteristic of this formalism is that the applicability of default (inference) rules can only be verified in the future of the reasoning process. We describe an interpretation of default logic in temporal epistemic logic which makes this characteristic explicit. It is shown that this interpretation yields a semantics for default logic based on temporal epistemic models. A comparison between the various semantics for default logic will show the differences and similarities of these approaches and ours.     

Alternating-time stream logic for multi-agent systems

Constraint automata have been introduced to provide a uniform operational model for specifying service interfaces of components, the network that yields the glue code for the components, and the operational behavior of the composite system. Constraint automata have been used as the basis for equivalence checking and model checking temporal logical properties. This paper presents a multi-player semantics for constraint automata which serves to reason about controllability, interaction and cooperation facilities of individual components or coalitions of components in a given network. We introduce a temporal logic framework, called alternating-time stream logic, that combines classical features of alternating-time logic (ATL) for concurrent games with special operators for specifying regular conditions on the data streams in the network and on the write and read operations at the I/O-ports of the components. Since constraint automata support any kind of synchronous and asynchronous peer-to-peer communication, the resulting game structure is non-standard and requires a series of nontrivial adaptations to the semantics and verification algorithms for classical alternating-time approaches.     

Enhanced high-level Petri nets with multiple colors for knowledgeverification/validation of rule-based expert systems

Exploring the properties of rule-based expert systems through Petri net models has received a lot of attention. Traditional Petri nets provide a straightforward but inadequate method for knowledge verification/validation of rule-based expert systems. We propose an enhanced high-level Petri net model in which variables and negative information can be represented and processed properly. Rule inference is modeled exactly and some important aspects in rule-based systems (RBSs), such as conservation of facts, refraction, and closed-world assumption, are considered in this model. With the coloring scheme proposed in this paper, the tasks involved in checking the logic structure and output correctness of an RES are formally investigated. We focus on the detection of redundancy, conflicts, cycles, unnecessary conditions, dead ends, and unreachable goals in an RES. These knowledge verification/validation (KVV) tasks are formulated as the reachability problem and improper knowledge can be detected by solving a set of equations with respect to multiple colors. The complexity of our method is discussed and a comparison of our model with other Petri net models is presented.     

BDI模型信念特性研究

Agent计算的典型模型是BDI(belief,desire,intention),信念是Agent计算的重要属性．把信念拓展为知识性信念和可实现信念．Agent的知识性信念是指Agent当前具有或掌握的知识,具有知识的进化和继承特性．Agent的可实现信念是指当前不成立而在将来会成立的事情,是Agent被意识到的个性倾向和目标．用非标准世界的模态逻辑为形式化工具描述两种信念,将可能世界的可达关系作为认识的不同阶段和达到可实现信念的不同阶段,避免了“逻辑全知问题”和逻辑蕴涵的副作用问题．可实现信念满足KD公理,知识性信念满足KDT4公理．两种信念适合描述Agent的意识状态和意识模型．     

Evidential bilattice logic and lexical inference

This paper presents an information-based logic that is applied to the analysis of entailment, implicature and presupposition in natural language. The logic is very fine-grained and is able to make distinctions that are outside the scope of classical logic. It is independently motivated by certain properties of natural human reasoning, namely partiality, paraconsistency, relevance, and defeasibility: once these are accounted for, the data on implicature and presupposition comes quite naturally.The logic is based on the family of semantic spaces known as bilattices, originally proposed by Ginsberg (1988), and used extensively by Fitting (1989, 1992). Specifically, the logic is based on a subset of bilattices that I call evidential bilattices, constructed as the Cartesian product of certain algebras with themselves. The specific details of the epistemic agent approach of the logical system is derived from the work of Belnap (1975, 1977), augmented by the use of evidential links for inferencing. An important property of the system is that it has been implemented using an extension of Fitting's work on bilattice logic programming (1989, 1991) to build a model-based inference engine for the augmented Belnap logic. This theorem prover is very efficient for a reasonably wide range of inferences.A shorter version of this material was originally presented at the Fifth International Symposium on Logic and Language, Noszvaj, Hungary, 1994. The author is now in the Mathematical Reasoning Group, Department of Artificial Intelligence, University of Edinburgh, 80 South Bridge, Edinburgh EH1 1HN, U.K.     

认识逻辑(1):关于知识和信念的逻辑框架

知识和信念是人工智能领域研究中经常涉及到的两个重要概念。本文讨论了知识和信念的涵义与关系，定义了认识逻辑系统ＥＩ，讨论了它的语法和语义，证明了认识逻辑ＥＬ不但是可靠的而且是完备的，认为逻辑ＥＬ不但可以用来描述人类的认识过程，还可以用于对常识推理以及分布式系统的形式化描述。