基于自适应模糊逻辑系统的一类混沌系统同步控制

针对一类带有未知函数和干扰的混沌系统,进行了基于自适应模糊逻辑系统的自适应同步控制器的设计。首先基于模糊逼近原理,通过对该混沌系统中未知函数的输入输出进行采样,根据采样数据信息设计出具有参数自适应功能的Mamdani型模糊逻辑系统;然后利用该模糊逻辑系统给出一种带有参数自适应的驱动响应同步控制器设计方法;最后通过数值仿真算例表明了该方法的有效性。     

Resource location in large scale heterogeneous and autonomous databases

In many large organizations there has been a proliferation of database systems to handle ever increasing volumes of information. In order to explore a potentially huge on-line information space, we must develop an architecture which allows for the dynamic data driven construction of inter-database node relationships in an incremental manner. In this paper we introduce the FINDIT architecture which uses informationmeta-types to provide a basis for such an organization and, consequently, provides a platform for interoperability. A distinction is made between theinformation andinter-node relationship spaces to achieve scalability. Tassili language primitives are used for the incremental building of dynamic inter-node relationships based upon usage considerations.     

Resolving contradictions: A plausible semantics for inconsistent systems

The purpose of a knowledge systemS is to represent the worldW faithfully. IfS turns out to be inconsistent containing contradictory data, its present state can be viewed as a result of information pollution with some wrong data. However, we may reasonably assume that most of the system content still reflects the world truthfully, and therefore it would be a great loss to allow a small contradiction to depreciate or even destroy a large amount of correct knowledge. So, despite the pollution,S must contain a meaningful subset, and so it is reasonable to assume (as adopted by many researchers) that the semantics of a logic system is determined by that of its maximally consistent subsets,mc-subsets. The information contained inS allows deriving certain conclusions regarding the truth of a formulaF inW. In this sense we say thatS contains a certain amount ofsemantic information and provides anevidence of F. A close relationship is revealed between the evidence, the quantity of semantic information of the system, and the set of models of its mc-subsets. Based on these notions, we introduce thesemantics of weighted mc-subsets as a way of reasoning in inconsistent systems. To show that this semantics indeed enables reconciling contradictions and deriving plausible beliefs about any statement including ambiguous ones, we apply it successfully to a series of justifying examples, such as chain proofs, rules with exceptions, and paradoxes.     

A second order theory of infinite trees

An axiomatic approach based on second order logic for specifying finite data types has been given in [12]. In the present paper we generalize the approach to infinite trees. Data logic CT of infinite trees is introduced and investigated. CT is based on the data logic T of finite trees. For treating infinite objects we heavily rely upon the notions of Bishop'apos;s constructive mathematics. Thus the results of the present paper are closely related with an intuitionistic type theory of infinite trees.     

Sophistication Revisited

Kolmogorov complexity measures the amount of information in a string as the size of the shortest program that computes the string. The Kolmogorov structure function divides the smallest program producing a string in two parts: the useful information present in the string, called sophistication if based on total functions, and the remaining accidental information. We formalize a connection between sophistication (due to Koppel) and a variation of computational depth (intuitively the useful or nonrandom information in a string), prove the existence of strings with maximum sophistication and show that they are the deepest of all strings.     

Kolmogorov Complexity and Information Theory. With an Interpretation in Terms of Questions and Answers

We compare the elementary theories of Shannon information and Kolmogorov complexity, the extent to which they have a common purpose, and wherethey are fundamentally different. We discuss and relate the basicnotions of both theories: Shannon entropy, Kolmogorov complexity, Shannon mutual informationand Kolmogorov (``algorithmic') mutual information. We explainhow universal coding may be viewed as a middle ground betweenthe two theories. We consider Shannon's rate distortion theory, whichquantifies useful (in a certain sense) information.We use the communication of information as our guiding motif, and we explain howit relates to sequential question-answer sessions.     

Enhancing accuracy and expressive power of range query answers over incomplete spatial databases via a novel reasoning approach

Modern spatial database applications built on top of distributed and heterogeneous spatial information sources such as conventional spatial databases underlying Geographical Information Systems (GIS), spatial data files and spatial information acquired or inferred from the Web, suffer from data integration and topological consistency problems. This more-and-more conveys in incomplete information, which makes answering range queries over incomplete spatial databases a leading research challenge in spatial database systems research. A significant instance of this setting is represented by the application scenario in which the geometrical information on a sub-set of spatial database objects is incomplete whereas the spatial database still stores topological relations among these objects (e.g., containment relations). Focusing on the spatial database application scenario above, in this paper we propose and experimentally assess a novel technique for efficiently answering range queries over incomplete spatial databases via integrating geometrical information and topological reasoning. We also propose I-SQE (Spatial Query Engine for Incomplete Information), an innovative query engine implementing this technique. Our proposed technique results not only effective but also efficient against both synthetic and real-life spatial data sets, and it finally allows us to enhance the quality and the expressive power of retrieved answers by meaningfully taking advantages from the amenity of representing spatial database objects via both the geometrical and the topological level.     

Information problem‐solving skills in small virtual groups and learning outcomes

This study investigated the frequency of use of information problem‐solving (IPS) skills and its relationship with learning outcomes. During the course of the study, 40 teachers carried out a collaborative IPS task in small virtual groups in a 4‐week online training course. The status of IPS skills was collected through self‐reports handed in over the course of the 4 weeks. Learning was evaluated by means of open‐ended questionnaires before and after the group task. Three types of knowledge learning were evaluated: declarative, procedural and situational. Teachers exhibited a recurrent use of all skills during the whole collaborative task, although periodic use differed from week to week. Results showed a relationship between some IPS skills and declarative and procedural knowledge. The skills that were statistically significant were share information, read peer's information and analyse information. Implications for learning support and instruction are discussed.     

Robust inference of trees

This paper is concerned with the reliable inference of optimal tree-approximations to the dependency structure of an unknown distribution generating data. The traditional approach to the problem measures the dependency strength between random variables by the index called mutual information. In this paper reliability is achieved by Walley's imprecise Dirichlet model, which generalizes Bayesian learning with Dirichlet priors. Adopting the imprecise Dirichlet model results in posterior interval expectation for mutual information, and in a set of plausible trees consistent with the data. Reliable inference about the actual tree is achieved by focusing on the substructure common to all the plausible trees. We develop an exact algorithm that infers the substructure in time O(m ⁴), m being the number of random variables. The new algorithm is applied to a set of data sampled from a known distribution. The method is shown to reliably infer edges of the actual tree even when the data are very scarce, unlike the traditional approach. Finally, we provide lower and upper credibility limits for mutual information under the imprecise Dirichlet model. These enable the previous developments to be extended to a full inferential method for trees.     

Brave induction: a logical framework for learning from incomplete information

This paper introduces a novel logical framework for concept-learning called brave induction. Brave induction uses brave inference for induction and is useful for learning from incomplete information. Brave induction is weaker than explanatory induction which is normally used in inductive logic programming, and is stronger than learning from satisfiability, a general setting of concept-learning in clausal logic. We first investigate formal properties of brave induction, then develop an algorithm for computing hypotheses in full clausal theories. Next we extend the framework to induction in nonmonotonic logic programs. We analyze computational complexity of decision problems for induction on propositional theories. Further, we provide examples of problem solving by brave induction in systems biology, requirement engineering, and multiagent negotiation.     

Constructive linear-time temporal logic: Proof systems and Kripke semantics

In this paper we study a version of constructive linear-time temporal logic (LTL) with the “next” temporal operator. The logic is originally due to Davies, who has shown that the proof system of the logic corresponds to a type system for binding-time analysis via the Curry-Howard isomorphism. However, he did not investigate the logic itself in detail; he has proved only that the logic augmented with negation and classical reasoning is equivalent to (the “next” fragment of) the standard formulation of classical linear-time temporal logic. We give natural deduction, sequent calculus and Hilbert-style proof systems for constructive LTL with conjunction, disjunction and falsehood, and show that the sequent calculus enjoys cut elimination. Moreover, we also consider Kripke semantics and prove soundness and completeness. One distinguishing feature of this logic is that distributivity of the “next” operator over disjunction “?(A∨B)⊃?A∨?B” is rejected in view of a type-theoretic interpretation.     

Resource-bounded sensing and planning in autonomous systems

This paper is concerned with the implications of limited computational resources and uncertainty on the design of autonomous systems. To address this problem, we redefine the principal role of sensor interpretation and planning processes. Following Agre and Chapman's plan-as-communication approach, sensing and planning are treated as computational processes that provide information to an execution architecture and thus improve the overall performance of the system. We argue that autonomous systems must be able to trade off the quality of this information with the computational resources required to produce it. Anytime algorithms, whose quality of results improves gradually as computation time increases, provide useful performance components for time-critical sensing and planning in robotic systems. In our earlier work, we introduced a compilation scheme for optimal composition of anytime algorithms. This paper demonstrates the applicability of the compilation technique to the construction of autonomous systems. The result is a flexible approach to construct systems that can operate robustly in real-time by exploiting the tradeoff between time and quality in planning, sensing and plan execution.     

基于时序逻辑证明编译优化程序变换的保义性

基于时序逻辑CTL(computation tree logic)的一种扩展CTL-FV对优化编译中的语句交换和变量替换这两种常见变换的保义性条件给出了形式刻画,采用含条件重写规则定义了保义语句交换T_exch和保义变量替换T_sub,并基于一种归纳证明框架对它们的保义性进行了证明.此外,基于变换Texch对程序基本块内保依赖语句重排的保义性也给出了一种构造性的证明.     

Model Checking Abilities of Agents: A Closer Look

Alternating-time temporal logic (atl) is a logic for reasoning about open computational systems and multi-agent systems. It is well known that atl model checking is linear in the size of the model. We point out, however, that the size of an atl model is usually exponential in the number of agents. When the size of models is defined in terms of states and agents rather than transitions, it turns out that the problem is (1) Δ ₃ ^P -complete for concurrent game structures, and (2) Δ ₂ ^P -complete for alternating transition systems. Moreover, for “Positive atl” that allows for negation only on the level of propositions, model checking is (1) Σ ₂ ^P -complete for concurrent game structures, and (2) NP-complete for alternating transition systems. We show a nondeterministic polynomial reduction from checking arbitrary alternating transition systems to checking turn-based transition systems, We also discuss the determinism assumption in alternating transition systems, and show that it can be easily removed. In the second part of the paper, we study the model checking complexity for formulae of atl with imperfect information (atl _ir ). We show that the problem is Δ ₂ ^P -complete in the number of transitions and the length of the formula (thereby closing a gap in previous work of Schobbens in Electron. Notes Theor. Comput. Sci. 85(2), 2004). Then, we take a closer look and use the same fine structure complexity measure as we did for atl with perfect information. We get the surprising result that checking formulae of atl _ir is also Δ ₃ ^P -complete in the general case, and Σ ₂ ^P -complete for “Positive atl _ir ”. Thus, model checking agents’ abilities for both perfect and imperfect information systems belongs to the same complexity class when a finer-grained analysis is used.     

Compositional and holistic quantum computational semantics

In quantum computational logic meanings of sentences are identified with quantum information quantities: systems of qubits or, more generally, mixtures of systems of qubits. We consider two kinds of quantum computational semantics: (1) a compositional semantics, where the meaning of a compound sentence is determined by the meanings of its parts; (2) a holistic semantics, which makes essential use of the characteristic “holistic” features of the quantum-theoretic formalism. We prove that the compositional and the holistic semantics characterize the same logic.     

On the expressiveness of MTL in the pointwise and continuous semantics

We show that the pointwise version of the logic MTL is strictly less expressive than the continuous version, over finitewords. The proof is constructive in that we exhibit a timed language, which is definable in the continuous semantics but is not definable in the pointwise semantics.     

Representing rules as random sets,II: Iterated rules

I. R. Goodman, H. T. Nguyen, and others have proposed the theory of random sets as a unifying paradigm for knowledge-based systems. The more types of ambiguous evidence that can be brought under the random-set umbrella, the more potentially useful the theory becomes as a systematic methodology for comparing and fusing seemingly incongruent kinds of information. Conditional event algebra provides a general framework for dealing with rule-based evidence in a manner consistent with probability theory. This and a previous companion article bring conditional event logic—and through it, rules and iterated rules—under the random set umbrella. In this article, we derive a new conditional event algebra, denoted GNW₂, for rules which are contingent on other rules. We show that this logic is the only one which extends the GNW first-degree logic, admits a simple embedding into random sets, and has GNW-like behavior. We show that GNW events are contained in a Boolean subalgebra GNW* of GNW₂. Finally, we show how GNW₂ can be used to recursively define a GNW-like Boolean logic for iterated rules of any degree. © 1996 John Wiley & Sons, Inc.