物件導向軟體之架構(Object-Oriented Software Construction)探討

Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaikos book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.

Ontology Matching

This chapter is devoted to a more detailed examination of game theory. Game theory is an important tool for analyzing strategic behavior, is concerned with how individuals make decisions when they recognize that their actions affect, and are affected by, the actions of other individuals or groups. Strategic behavior recognizes that the decision-making process is frequently mutually interdependent. Game theory is the study of the strategic behavior involving the interaction of two or more individuals, teams, or firms, usually referred to as players. Two game theoretic scenarios were examined in this chapter: Simultaneous-move and multi-stage games. In simultaneous-move games the players effectively move at the same time. A normal-form game summarizes the players, possible strategies and payoffs from alternative strategies in a simultaneous-move game. Simultaneous-move games may be either noncooperative or cooperative. In contrast to noncooperative games, players of cooperative games engage in collusive behavior. A Nash equilibrium, which is a solution to a problem in game theory, occurs when the players’ payoffs cannot be improved by changing strategies. Simultaneous-move games may be either one-shot or repeated games. One-shot games are played only once. Repeated games are games that are played more than once. Infinitely-repeated games are played over and over again without end. Finitely-repeated games are played a limited number of times. Finitely-repeated games have certain or uncertain ends.

An Introduction to Game Theory

Multiagent Systems is the title of a collection of papers dedicated to surveying specific themes of Multiagent Systems (MAS) and Distributed Artificial Intelligence (DAI). All of them authored by leading researchers of this dynamic multidisciplinary field.

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Multiagent systems: a modern approach to distributed artificial intelligence

Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications. 

Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on developing useful and reusable models, this market-leading book explains how to build semantic content (ontologies) and how to build applications that access that content.

New in this edition: 


Coverage of the latest Semantic Web tools for organizing, querying, and processing information - see details in TOC below

Detailed information on the latest ontologies used in key web applications including ecommerce, social networking, data mining, using government data, and more




Updated with the latest developments and advances in Semantic Web technologies for organizing, querying, and processing information, including SPARQL, RDF and RDFS, OWL 2.0, and SKOS 
Detailed information on the ontologies used in today's key web applications, including ecommerce, social networking, data mining, using government data, and more 
Even more illustrative examples and case studies that demonstrate what semantic technologies are and how they work together to solve real-world problems

Table of Contents

1?What Is The Semantic Web?
2?Semantic Modeling
3?RDF - The Basis of the Semantic Web
4?SPARQL - The Query Language for RDF
5?Semantic Web Application Architecture
6?RDF And Inferencing
7?RDF Schema Language
8?RDFS-Plus
9?SKOS - the Simple Knowledge Organization System
10?Ontologies in the Wild: Linked Open Data and the Open Graph Project
11?Basic OWL
12?Counting and Sets In OWL 
13?MORE Ontologies in the Wild: QUDT, GoodRelations, and OBO Foundry
14?Good and Bad Modeling Practices 
15?OWL 2.0 Levels and Logic
16?Conclusions
17?Frequently Asked Questions

Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL

The Future of the Internet- Concepts- Ontology in Computer Science- Knowledge Representation in Description Logic- RDF and RDF Schema- OWL- Rule Languages- Semantic Web Services- Technologies- Methods for Ontology Development- Ontology Sources- Semantic Web Software Tools- Applications- Software Agents- Semantic Desktop- Ontology Applications in Art- Geospatial Semantic Web

Semantic Web: Concepts, Technologies and Applications

This paper describes an approach to ontology negotiation between agents supporting intelligent information management. Ontologies are declarative (data-driven) expressions of an agent's “world”: the objects, operations, facts and rules that constitute the logical space within which an agent performs. Ontology negotiation enables agents to cooperate in performing a task, even if they are based on different ontologies.Our objective is to increase the opportunities for “strange agents” – that is, agents not necessarily developed within the same framework or with the same contextual operating assumptions – to communicate in solving tasks when they encounter each other on the web. In particular, we have focused on information search tasks.We have developed a protocol that allows agents to discover ontology conflicts and then, through incremental interpretation, clarification and explanation, establish a common basis for communicating with each other. We have implemented this protocol in a set of Java classes that can be added to a variety of agents, irrespective of their underlying ontological assumptions. We have demonstrated the use of the protocol, through this implementation, in a test-bed that includes two large scientific archives: NASA's Global Change Master Directory and NOAA's Wind and Sea Index.This paper presents an overview of different methods for resolving ontology mismatches and motivates the Ontology Negotiation Protocol (ONP) as a method that addresses some problems with other approaches. Much remains to be done. The protocol must be tested in larger and less familiar contexts (for example, numerous archives that have not been preselected) and it must be extended to accommodate additional forms of clarification and ontology evolution.

Ontology negotiation between intelligent information agents

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Autonomous and Autonomic Systems: With Applications to NASA Intelligent Spacecraft Operations and Exploration Systems

A reconfigurable space filling robotic architecture has a wide range of possible applications. One of the more intriguing possibilities is mobility in very irregular and otherwise impassable terrain. NASA Goddard Space Flight Center is developing the third generation of its addressable reconfigurable technology (ART) tetrahedral robotics architecture. An ART-based variable geometry truss consisting of 12 tetrahedral elements made from 26 smart struts on a wireless network has been developed. The primary goal of this development is the demonstration of a new kind of robotic mobility that can provide access and articulation that complement existing capabilities. An initial set of gaits and other behaviors are being tested, and accommodations for payloads such as sensor and telemetry packages are being studied. Herein, we describe our experience with the ART tetrahedral robotics architecture and the improvements implemented in the third generation of this technology. Applications of these robots to space exploration and the tradeoffs involved with this architecture will be discussed.

Tetrahedral Robotics for Space Exploration

NASA's drive toward realizing higher levels of autonomy, in both its ground and space systems, is supporting an active and growing interest in agent technology. This paper will address the expanding research in this exciting technology area.

As examples of current work, the Lights-Out Ground Operations System (LOGOS), under prototyping at the Goddard Space Flight Center (GSFC), and the spacecraft-oriented Remote Agent project under development at the Ames Research Center (ARC) and the Jet Propulsion Laboratory (JPL) will be presented.

Walt Truszkowski

Papers

Semantic Web: Concepts, Technologies and Applications

Ontology negotiation between intelligent information agents

Autonomous and Autonomic Systems: With Applications to NASA Intelligent Spacecraft Operations and Exploration Systems

Tetrahedral Robotics for Space Exploration

Agent technology from a NASA perspective