457,983 research outputs found

    Agent Assistance: From Problem Solving to Music Teaching

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    We report on our research on agents that act and behave in a web learning environment. This research is part of a general approach to agents acting and behaving in virtual environments where they are involved in providing information, performing transactions, demonstrating products and, more generally, assisting users or visitors of the web environment in doing what they want or have been asked to do. While initially we hardly provided our agents with 'teaching knowledge', we now are in the process of making such knowledge explicit, especially in models that take into account that assisting and teaching takes place in a visualized and information-rich environment. Our main (embodied) tutor-agent is called Jacob; it knows about the Towers of Hanoi, a well-known problem that is offered to CS students to learn about recursion. Other agents we are working on assist a visitor in navigating in a virtual world or help the visitor in getting information. We are now designing a music teacher - using knowledge of software engineering and how to design multi-modal interactions, from previous projects

    Knowledge Channels: Bringing the Knowledge on the Web to Software Agents

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    In this paper, we present a new framework to extract knowledge from today’s non-semantic web. It associates semantics with the information extracted, which improves agent interoperability; it can also deal with changes to the structure of a web page, which improves adaptability; furthermore, it achieves to delegate the knowledge extraction procedure to specialist agents, easing software development and promoting software reuse and maintainability.Comisión Interministerial de Ciencia y Tecnología TIC 2000–1106–C02–01Comisión Interministerial de Ciencia y Tecnología FIT-150100-2001-7

    On the convergence of autonomous agent communities

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    This is the post-print version of the final published paper that is available from the link below. Copyright @ 2010 IOS Press and the authors.Community is a common phenomenon in natural ecosystems, human societies as well as artificial multi-agent systems such as those in web and Internet based applications. In many self-organizing systems, communities are formed evolutionarily in a decentralized way through agents' autonomous behavior. This paper systematically investigates the properties of a variety of the self-organizing agent community systems by a formal qualitative approach and a quantitative experimental approach. The qualitative formal study by applying formal specification in SLABS and Scenario Calculus has proven that mature and optimal communities always form and become stable when agents behave based on the collective knowledge of the communities, whereas community formation does not always reach maturity and optimality if agents behave solely based on individual knowledge, and the communities are not always stable even if such a formation is achieved. The quantitative experimental study by simulation has shown that the convergence time of agent communities depends on several parameters of the system in certain complicated patterns, including the number of agents, the number of community organizers, the number of knowledge categories, and the size of the knowledge in each category

    On the emergent Semantic Web and overlooked issues

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    The emergent Semantic Web, despite being in its infancy, has already received a lotof attention from academia and industry. This resulted in an abundance of prototype systems and discussion most of which are centred around the underlying infrastructure. However, when we critically review the work done to date we realise that there is little discussion with respect to the vision of the Semantic Web. In particular, there is an observed dearth of discussion on how to deliver knowledge sharing in an environment such as the Semantic Web in effective and efficient manners. There are a lot of overlooked issues, associated with agents and trust to hidden assumptions made with respect to knowledge representation and robust reasoning in a distributed environment. These issues could potentially hinder further development if not considered at the early stages of designing Semantic Web systems. In this perspectives paper, we aim to help engineers and practitioners of the Semantic Web by raising awareness of these issues

    WSIA: web ontological search engine based on smart agents applied to scientific articles

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    The Semantic Web proposed by the W3C (Word Wide Web Consortium), aims to make the automation of the information contained in the current web through semantic processing based on ontologies that define what must be the rules used for the representation knowledge. This article resulting from the research project “Model for the representation of knowledge based on Web ontologies and intelligent search agents, if required: Scientific articles WSIA” proposes an architecture for finding information through intelligent agents and ontologies Web of scientific articles. This paper shows the architecture, implementation and comparing these with traditional applications

    Towards engineering ontologies for cognitive profiling of agents on the semantic web

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    Research shows that most agent-based collaborations suffer from lack of flexibility. This is due to the fact that most agent-based applications assume pre-defined knowledge of agents’ capabilities and/or neglect basic cognitive and interactional requirements in multi-agent collaboration. The highlight of this paper is that it brings cognitive models (inspired from cognitive sciences and HCI) proposing architectural and knowledge-based requirements for agents to structure ontological models for cognitive profiling in order to increase cognitive awareness between themselves, which in turn promotes flexibility, reusability and predictability of agent behavior; thus contributing towards minimizing cognitive overload incurred on humans. The semantic web is used as an action mediating space, where shared knowledge base in the form of ontological models provides affordances for improving cognitive awareness

    Evaluating Knowledge Representation and Reasoning Capabilites of Ontology Specification Languages

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    The interchange of ontologies across the World Wide Web (WWW) and the cooperation among heterogeneous agents placed on it is the main reason for the development of a new set of ontology specification languages, based on new web standards such as XML or RDF. These languages (SHOE, XOL, RDF, OIL, etc) aim to represent the knowledge contained in an ontology in a simple and human-readable way, as well as allow for the interchange of ontologies across the web. In this paper, we establish a common framework to compare the expressiveness of "traditional" ontology languages (Ontolingua, OKBC, OCML, FLogic, LOOM) and "web-based" ontology languages. As a result of this study, we conclude that different needs in KR and reasoning may exist in the building of an ontology-based application, and these needs must be evaluated in order to choose the most suitable ontology language(s)

    Improving the professional knowledge base for education: Using knowledge management (KM) and Web 2.0 tools

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    Improving education systems is an elusive goal. Despite considerable investment, international studies such as the OECD Teaching and Learning International Survey (TALIS) project and the McKinsey Report How the world’s best performing schools come out on top indicate that improving teacher quality is more important than increased financial investment. Both reports challenge governments, academics and practitioners to adopt new ways of sharing and building knowledge. This paper makes the case for national education systems to adopt tried and tested knowledge management and web 2.0 tools used by other sectors and highlights the neglected potential of teacher educators as agents for improvement
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