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Intelligent Systems, IEEE

Issue 4 • Date July-Aug. 2004

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Displaying Results 1 - 16 of 16
  • [Front cover]

    Page(s): c1
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    Freely Available from IEEE
  • Table of contents

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    Freely Available from IEEE
  • A new generation of military robots

    Page(s): 2 - 3
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    US military branches are undergoing a shift in the structure and missions that's designed to help them become lighter and more agile, able to move easily and quickly to hot spots. Long-range planning to prepare for modern warfare includes developing robotics for military use. For instance, the Army's Future Combat Systems program plans to make a third of its ground forces robotic within about 15 years. The army's 20-year plan envisions 10 steps of robotic development, starting with completely human-controlled systems and ending with autonomous, armed, cooperative robots. The Robotics Institute has developed a small, unmanned ground vehicle called a "throwbot" that can be tossed into buildings to gather and relay information back to soldiers before they enter the building. The institute is also developing larger robotic vehicles that can do reconnaissance and breaching missions, including a robotic helicopter that can generate 3D models from the air. View full abstract»

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  • Ontology versioning in an ontology management framework

    Page(s): 6 - 13
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    Ontologies have become ubiquitous in information systems. They constitute the semantic Web's backbone, facilitate e-commerce, and serve such diverse application fields as bioinformatics and medicine. As ontology development becomes increasingly widespread and collaborative, developers are creating ontologies using different tools and different languages. These ontologies cover unrelated or overlapping domains at different levels of detail and granularity. A uniform framework, which we present here, helps users manage multiple ontologies by leveraging data and algorithms developed for one tool in another. For example, by using an algorithm we developed for structural evaluation of ontology versions, this framework lets developers compare different ontologies and map similarities and differences among them. Multiple-ontology management includes these tasks: maintain ontology libraries, import and reuse ontologies, translate ontologies from one formalism to another, support ontology versioning, specify transformation rules between different ontologies and version, merge ontologies, align and map between ontologies, extract an ontology's self-contained parts, support inference across multiple ontologies, support query across multiple ontologies. View full abstract»

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  • Automatically composed workflows for grid environments

    Page(s): 16 - 23
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    Once the realm of high-performance computing for scientific applications, grid computing is rising as a key enabling infrastructure for resource sharing and coordinated problem solving in dynamic multiinstitutional virtual organizations. Grids build over networking technology to provide middleware support such as locating files over a network of computers, scheduling the distributed execution of jobs, and managing resource sharing and access policies.2 The need of scientific communities to interconnect applications, data, expertise, and computing resources is shared by other application areas, such as business, government, medical care, and education. View full abstract»

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  • ODE SWS: a framework for designing and composing semantic Web services

    Page(s): 24 - 31
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    Specifying semantic Web services requires designing the semantic description at a conceptual level to guarantee its correctness and avoid inconsistencies. We present a framework for designing and composing semantic Web services at the knowledge level in a language-independent manner. We base our framework on a stack of ontologies that explicitly describes different semantic Web services features, and on the assumption that the semantic Web services are modeled as problem-solving methods (PSMs) that describe the service's internal structure. View full abstract»

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  • KAoS policy management for semantic Web services

    Page(s): 32 - 41
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    Web Services power through explicit representations of Web resources underlying semantics and the development of an intelligent Web infrastructure that can fully exploit them. Semantic Web languages, such as OWL, extend RDF to let users specify ontologies comprising taxonomies of classes and inference rules. Both people and software agents can effectively use Semantic Web Services.' Agents will increasingly use the combination of semantic markup languages and Semantic Web Services to understand and autonomously manipulate Web content in significant ways. Agents will discover, communicate, and cooperate with other agents and services and-as we' 11 describe -will rely on policy-based management and control mechanisms to ensure respect for human-imposed constraints on agent interaction. Policy-based controls of Semantic Web Services can also help govern interaction with traditional (nonagent) clients. View full abstract»

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  • Filtering and selecting semantic Web services with interactive composition techniques

    Page(s): 42 - 49
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    To demonstrate the utility of semantic Web service descriptions for service composition, we've developed a goal-oriented, interactive composition approach that uses matchmaking algorithms to help users filter and select services while building the composition. filtering and selecting services helps the user drive the composition process. We've implemented composition. Indeed, it is the filtering and selection of services that helps the user drive these ideas in a prototype system that can compose the Web services deployed on the Internet and provide filtering capabilities where a large number of similar services might be available. View full abstract»

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  • Authorization and privacy for semantic Web services

    Page(s): 50 - 56
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    Web services will soon handle users' private information. They'll need to provide privacy guarantees to prevent this delicate information from ending up in the wrong hands. More generally, Web services will need to reason about their users' policies that specify who can access private information and under what conditions. These requirements are even more stringent for semantic Web services that exploit the semantic Web to automate their discovery and interaction because they must autonomously decide what information to exchange and how. In our previous work, we proposed ontologies for modeling the high-level security requirements and capabilities of Web services and clients.1 This modeling helps to match a client's request with appropriate services-those based on security criteria as well as functional descriptions. View full abstract»

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  • Value Webs: using ontologies to bundle real-world services

    Page(s): 57 - 66
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    Real-world services - that is, nonsoftware-based services - differ significantly from Web services, usually defined as software functionality accessible and configurable over the Web. Because of the economic, social, and business importance of the service concept in general, we believe it's necessary to rethink what this concept means in an ontological and computational sense. We deal about the OBELIX (ontology-based electronic integration of complex products and value chains) project has therefore developed a generic component-based ontology for real-world services. This OBELIX service ontology is first of all a formalization of concepts that represent the consensus in the business science literature on service management and marketing. We express our service ontology in a graphical, network-style representation, and we've developed support tools that facilitate end-user modeling of services. Then, automated knowledge-based configuration methods let business designers and analysts analyze service bundles. We've tested our ontology, methods, and tools on applications in real-world case studies of different industry sectors. View full abstract»

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  • Dynamic invocation of semantic Web services that use unfamiliar ontologies

    Page(s): 67 - 73
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    The semantic Web research community has developed ontologies and languages for semantically describing Web services. For example, OWL-S is an ontology developed using the OWL semantic Web description language. The purpose of OWL-S, formerly DAML-S, is to describe Web services so that software agents can read these descriptions and reason about how to interact with the services they describe. These efforts aim to facilitate interactions with services when the client agents lack built-in code for invoking those services' APIs&just as people can effectively use Web sites they've found through search engines. For example, without any reprogramming, a software system could have the flexibility to use various services that do the same kind of job but have different APIs. This can be useful in a number of situations, such as when a familiar service's API has changed or when the API is unavailable but a discovered new service could do the job. These semantic service descriptions also make it easier to compose services, by enabling reasoning about how to transform one service's outputs into another's inputs. View full abstract»

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  • Why evaluate ontology technologies? Because it works!

    Page(s): 74 - 81
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    We deal with two types of ontology evaluation, content evaluation and ontology technology evaluation. Evaluating content is a must for preventing applications from using inconsistent, incorrect, or redundant ontologies. It's unwise to publish an ontology that one or more software applications will use without first evaluating it. A well-evaluated ontology won't guarantee the absence of problems, but it makes its use safer. Similarly, evaluating ontology technology eases its integration with other software environments, ensuring a correct technology transfer from the academic to the industrial world. We also discuss ontology libraries, ontology tool, and formal evaluation of ontology quality. View full abstract»

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  • Artificial societies for integrated and sustainable development of metropolitan systems

    Page(s): 82 - 87
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    Unfortunately, we can't solve transportation problems by focusing on transportation systems alone. Rather, we must consider the combined effects with other metropolitan systems. Artificial systems, based on artificial societies and agent-modeling technology, are effective tools for this purpose. Metropolitan transportation, logistics, and ecosystems are intrinsically open, dynamic, unpredictable, and complex in their behaviors and effects. We must adopt a management and control strategy for those systems based on continuous investigation and improvement and should use computational experiments with artificial systems to overcome the difficulty of experimenting with real systems. View full abstract»

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  • What is design in the context of human-centered computing?

    Page(s): 89 - 95
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    We deal about the design in human-centered computing. Problem solving often involves recognizing and fiddling with tacit assumptions. Such realization can often come from seeing things from new perspectives. Appreciating the human-centered perspective may offer some hope for enriching design's scientific foundations and for crafting new and better approaches to it. Certainly this suggests a constraint on or a goal for design, but how do we go from such statements to actual designs that accomplish the stated goals? We approach this class of question by considering the origins of and historical influences on the notion of design, then by considering the assumptions underlying our modern conception of design in light of the principles of human-centered computing. View full abstract»

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  • Al in Australia and New Zealand

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    We provide an overview of Al in Australia and New Zealand, we also offer snapshots of Al research throughout the region's institutes and universities and review its industry and conference activities. Australia's Commonwealth Scientific and Industrial Research Organization is one of the world's largest and most diverse scientific global research organizations, and many of its discipline groups are researching and applying Al. For example, a CSIRO group in Canberra is leveraging worldwide Semantic Web initiatives while researching ways to share scientific knowledge in cross-institutional communities. The group aims to combine various approaches-Al approaches to semantic service description, database approaches to distributed data management, and Web services approaches to interoperability-to rapidly assemble customized software applications from large-scale heterogeneous resource components. View full abstract»

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Aims & Scope

IEEE Intelligent Systems serves users, managers, developers, researchers, and purchasers who are interested in intelligent systems and artificial intelligence, with particular emphasis on applications.

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Meet Our Editors

Editor-in-Chief
Daniel Zeng
University of Arizona