We address the problem of answering Web ontology queries efficiently. An ontology is formalized as a deductive ontology base (DOB), a deductive database that comprises the ontology's inference axioms and facts. A cost-based query optimization technique for DOB is presented. A hybrid cost model is proposed to estimate the cost and cardinality of basic and inferred facts. Cardinality and cost of inferred facts are estimated using an adaptive sampling technique, while techniques of traditional relational cost models are used for estimating the cost of basic facts and conjunctive ontology queries. Finally, we implement a dynamic-programming optimization algorithm to identify query evaluation plans that minimize the number of intermediate inferred facts. We modeled a subset of the Web ontology language Lite as a DOB and performed an experimental study to analyze the predictive capacity of our cost model and the benefits of the query optimization technique. Our study has been conducted over synthetic and real-world Web ontology language ontologies and shows that the techniques are accurate and improve query performance.

The historical design of the call-by-value theory of control relies on the reification of evaluation contexts as regular functions and on the use of ordinary term application for jumping to a continuation. To the contrary, the control calculus, developed by the authors, distinguishes between jumps and terms. This alternative calculus, which derives from Parigot's λμ-calculus, works by direct structural substitution of evaluation contexts. We review and revisit the legacy theories of control and argue that provides an observationally equivalent but smoother theory. In an additional note contributed by Matthias Felleisen, we review the story of the birth of control calculi during the mid- to late-eighties at Indiana University.

Babai and Sós have asked whether there exists a constant c > 0 such that every finite group G has a product-free subset of size at least c|G|: that is, a subset X that does not contain three elements x, y and z with xy = z. In this paper we show that the answer is no. Moreover, we give a simple sufficient condition for a group not to have any large product-free subset.

Due to the existence of singular configurations within the workspace for a platform- type parallel manipulator (PPM), the actuating force demands increase drastically as the PPM approaches or crosses singular points. Therefore, in this report, a numerical technique is presented to plan a singularity-free trajectory of the PPM for minimum actuating effort and reactions. By using the parametric trajectory representation, the singularity-free trajectory planning problem can be cast to the determination of undetermined control points, after which a particle swarm optimization algorithm is employed to find the optimal control points. This algorithm ensures that the obtained trajectories can avoid singular points within the workspace and that the PPM has the minimum actuating effort and reactions. Simulations and discussions are presented to demonstrate the effectiveness of the algorithm.

Two distributed stochastic search algorithms are proposed for motion planning of multi-robot systems: (i) distributed gradient, (ii) swarm intelligence theory. Distributed gradient consists of multiple stochastic search algorithms that start from different points in the solutions space and interact with each other while moving toward the goal position. Swarm intelligence theory is a derivative-free approach to the problem of multi-robot cooperation which works by searching iteratively in regions defined by each robot's best previous move and the best previous move of its neighbors. The performance of both approaches is evaluated through simulation tests.

Extensible Markup Language (XML) is a simple, very flexible text format derived from SGML. Originally designed to meet the challenges of large-scale electronic publishing, XML is also playing an increasingly important role in the exchange of a wide variety of data on the Web and elsewhere. XPath language is the result of an effort to provide address parts of an XML document. In support of this primary purpose, it becomes in a query language against an XML document. In this paper we present a proposal for the implementation of the XPath language in logic programming. With this aim we will describe the representation of XML documents by means of a logic program. Rules and facts can be used for representing the document schema and the XML document itself. In particular, we will present how to index XML documents in logic programs: rules are supposed to be stored in main memory, however facts are stored in secondary memory by using two kind of indexes: one for each XML tag, and other for each group of terminal items. In addition, we will study how to query by means of the XPath language against a logic program representing an XML document. It evolves the specialization of the logic program with regard to the XPath expression. Finally, we will also explain how to combine the indexing and the top-down evaluation of the logic program.

There are two ways to write a program for manipulating tree-structured data such as XML documents: One is to write a tree-processing program focusing on the logical structure of the data and the other is to write a stream-processing program focusing on the physical structure. While tree-processing programs are easier to write than stream-processing programs, tree-processing programs are less efficient in memory usage since they use trees as intermediate data. Our aim is to establish a method for automatically translating a tree-processing program to a stream-processing one in order to take the best of both worlds. We first define a programming language for processing binary trees and a type system based on ordered linear type, and show that every well-typed program can be translated to an equivalent stream-processing program. We then extend the language and the type system to deal with XML documents. We have implemented an XML stream processor generator based on our algorithm, and obtained promising experimental results.

Building rules on top of ontologies is the ultimate goal of the logical layer of the Semantic Web. To this aim, an ad-hoc markup language for this layer is currently under discussion. It is intended to follow the tradition of hybrid knowledge representation and reasoning systems, such as -log that integrates the description logic and the function-free Horn clausal language Datalog. In this paper, we consider the problem of automating the acquisition of these rules for the Semantic Web. We propose a general framework for rule induction that adopts the methodological apparatus of Inductive Logic Programming and relies on the expressive and deductive power of -log. The framework is valid whatever the scope of induction (description versus prediction) is. Yet, for illustrative purposes, we also discuss an instantiation of the framework which aims at description and turns out to be useful in Ontology Refinement.

The following two conjectures arose in the work of Grimmett and Winkler, and Pemantle: the uniformly random forest F and the uniformly random connected subgraph C of a finite graph G have the edge-negative association property. In other words, for all distinct edges e and f of G, the probability that F (respectively, C) contains e conditioned on containing f is less than or equal to the probability that F (respectively, C) contains e. Grimmett and Winkler showed that the first conjecture is true for all simple graphs on 8 vertices and all graphs on 9 vertices with at most 18 edges. In this paper, we describe an infinite, nontrivial class of graphs and matroids for which a generalized version of both conjectures holds.

We obtain large-deviation approximations for the empirical distribution for a general family of occupancy problems. In the general setting, balls are allowed to fall in a given urn depending on the urn's contents prior to the throw. We discuss a parametric family of statistical models that includes Maxwell–Boltzmann, Bose–Einstein and Fermi–Dirac statistics as special cases. A process-level large-deviation analysis is conducted and the rate function for the original problem is then characterized, via the contraction principle, by the solution to a calculus of variations problem. The solution to this variational problem is shown to coincide with that of a simple finite-dimensional minimization problem. As a consequence, the large-deviation approximations and related qualitative information are available in more-or-less explicit form.

This work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.

Given a digraph D, let δ0(D) := min{δ+(D), δ−(D)} be the minimum semi-degree of D. We show that every sufficiently large digraph D with δ0(D)≥n/2 + l −1 is l-linked. The bound on the minimum semi-degree is best possible and confirms a conjecture of Manoussakis [17]. We also determine the smallest minimum semi-degree which ensures that a sufficiently large digraph D is k-ordered, i.e., that for every sequence s1, . . ., sk of distinct vertices of D there is a directed cycle which encounters s1, . . ., sk in this order. This result will be used in [16].

We are researching the interaction between the rule and the ontology layers of the Semantic Web, by comparing two options: 1) using OWL and its rule extension SWRL to develop an integrated ontology/rule language, and 2) layering rules on top of an ontology with RuleML and OWL. Toward this end, we are developing the SWORIER system, which enables efficient automated reasoning on ontologies and rules, by translating all of them into Prolog and adding a set of general rules that properly capture the semantics of OWL. We have also enabled the user to make dynamic changes on the fly, at run time. This work addresses several of the concerns expressed in previous work, such as negation, complementary classes, disjunctive heads, and cardinality, and it discusses alternative approaches for dealing with inconsistencies in the knowledge base. In addition, for efficiency, we implemented techniques called extensionalization, avoiding reanalysis, and code minimization.

Family polymorphism has been proposed for object-oriented languages as a solution to supporting reusable yet type-safe mutually recursive classes. A key idea of family polymorphism is the notion of families, which are used to group mutually recursive classes. In the original proposal, due to the design decision that families are represented by objects, dependent types had to be introduced, resulting in a rather complex type system. In this article, we propose a simpler solution of lightweight family polymorphism, based on the idea that families are represented by classes rather than by objects. This change makes the type system significantly simpler without losing much expressive power of the language. Moreover, “family-polymorphic” methods now take a form of parametric methods; thus, it is easy to apply method type argument inference as in Java 5.0. To rigorously show that our approach is safe, we formalize the set of language features on top of Featherweight Java and prove that the type system is sound. An algorithm for type inference for family-polymorphic method invocations is also formalized and proved to be correct. Finally, a formal translation by erasure to Featherweight Java is presented; it is proved to preserve typing and execution results, showing that our new language features can be implemented in Java by simply extending the compiler.

Prolog is an excellent tool for representing and manipulating data written in formal languages as well as natural language. Its safe semantics and automatic memory management make it a prime candidate for programming robust Web services. Although Prolog is commonly seen as a component in a Web application that is either embedded or communicates using a proprietary protocol, we propose an architecture where Prolog communicates to other components in a Web application using the standard HTTP protocol. By avoiding embedding in external Web servers, development and deployment become much easier. To support this architecture, in addition to the transfer protocol, we must also support parsing, representing and generating the key Web document types such as HTML, XML and RDF. This article motivates the design decisions in the libraries and extensions to Prolog for handling Web documents and protocols. The design has been guided by the requirement to handle large documents efficiently. The described libraries support a wide range of Web applications ranging from HTML and XML documents to Semantic Web RDF processing. The benefits of using Prolog for Web-related tasks are illustrated using three case studies.

Let be a sequence of real numbers satisfying for each k ≥ 0, where M ≥ 1 is a fixed number. We prove that, for any sequence of real numbers , there is a real number ξ such that for each k ≥ 0. Here, denotes the distance from to the nearest integer. This is a corollary derived from our main theorem, which is a more general matrix version of this statement with explicit constants.

The Semantic Web drives toward the use of the Web for interacting with logically interconnected data. Through knowledge models such as Resource Description Framework (RDF), the Semantic Web provides a unifying representation of richly structured data. Adding logic to the Web implies the use of rules to make inferences, choose courses of action, and answer questions. This logic must be powerful enough to describe complex properties of objects but not so powerful that agents can be tricked by being asked to consider a paradox. The Web has several characteristics that can lead to problems when existing logics are used, in particular, the inconsistencies that inevitably arise due to the openness of the Web, where anyone can assert anything. N3Logic is a logic that allows rules to be expressed in a Web environment. It extends RDF with syntax for nested graphs and quantified variables and with predicates for implication and accessing resources on the Web, and functions including cryptographic, string, math. The main goal of N3Logic is to be a minimal extension to the RDF data model such that the same language can be used for logic and data. In this paper, we describe N3Logic and illustrate through examples why it is an appropriate logic for the Web.

In this paper, we present a novel structure of a snake-like robot. This structure enables passive locomotion in snake-like robots. Dynamic equations are obtained for motion in a horizontal plane, using Gibbs–Appell method. Kinematic model of the robot include numerous nonholonomic constraints, which can be omitted at the beginning by choosing proper coordinates to describe the model in Gibbs–Appell framework. In such a case, dynamic equations will be significantly simplified, resulting in considerable reduction of simulation time. Simulation results show that, by proper selection of initial conditions, joint angles operate in a limit cycle and robot can locomote steadily on a passive trajectory. It can be seen that the passive trajectory is approximately a Serpenoid curve.

Recently, there has been a lot of interest in the integration of Description Logics (DL) and rules on the Semantic Web. We define guarded hybrid knowledge bases (or g-hybrid knowledge bases) as knowledge bases that consist of a Description Logic knowledge base and a guarded logic program, similar to the + log knowledge bases from Rosati (In Proceedings of the 10th International Conference on Principles of Knowledge Representation and Reasoning, AAAI Press, Menlo Park, CA, 2006, pp. 68–78.). g-Hybrid knowledge bases enable an integration of Description Logics and Logic Programming where, unlike in other approaches, variables in the rules of a guarded program do not need to appear in positive non-DL atoms of the body, i.e., DL atoms can act as guards as well. Decidability of satisfiability checking of g-hybrid knowledge bases is shown for the particular DL , which is close to OWL DL, by a reduction to guarded programs under the open answer set semantics. Moreover, we show 2-Exptime-completeness for satisfiability checking of such g-hybrid knowledge bases. Finally, we discuss advantages and disadvantages of our approach compared with + log knowledge bases.

We describe a short and easy-to-analyse construction of constant-degree expanders. The construction relies on the replacement product, applied by Reingold, Vadhan and Wigderson (2002) to give an iterative construction of bounded-degree expanders. Here we give a simpler construction, which applies the replacement product (only twice!) to turn the Cayley expanders of Alon and Roichman (1994), whose degree is polylog n, into constant-degree expanders. This enables us to prove the required expansion using a simple new combinatorial analysis of the replacement product (instead of the spectral analysis used by Reingold, Vadhan and Wigderson).