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International Conference on Intelligent Virtual Agents

IVA 2016: Intelligent Virtual Agents pp 475–478Cite as

A Distributed Intelligent Agent Approach to Context in Information Retrieval

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10011))

Abstract

Information retrieval across disadvantaged networks requires intelligent agents that can make decisions about what to transmit in such a way as to minimize network performance impact while maximizing utility and quality of information (QOI). Specialized agents at the source need to process unstructured, ad-hoc queries, identifying both the context and the intent to determine the implied task. Knowing the task will allow the distributed agents that service the requests to filter, summarize, or transcode data prior to responding, lessening the network impact. This paper describes an approach that uses natural language processing (NLP) techniques, multi-valued logic based inferencing, distributed intelligent agents, and task-relevant metrics for information retrieval.

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Author information

Authors and Affiliations

  1. Army Research Laboratory, Adelphi, MD, USA

    Reginald L. Hobbs

Authors
  1. Reginald L. Hobbs
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Corresponding author

Correspondence to Reginald L. Hobbs .

Editor information

Editors and Affiliations

  1. University of Southern California, Los Angeles, California, USA

    David Traum

  2. University of Southern California, Los Angeles, California, USA

    William Swartout

  3. US Army Research Laboratory, Los Angeles, California, USA

    Peter Khooshabeh

  4. Universität Bielefeld, Bielefeld, Nordrhein-Westfalen, Germany

    Stefan Kopp

  5. University of Southern California, Los Angeles, California, USA

    Stefan Scherer

  6. University of Southern California, Los Angeles, California, USA

    Anton Leuski

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© 2016 Springer International Publishing AG

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Hobbs, R.L. (2016). A Distributed Intelligent Agent Approach to Context in Information Retrieval. In: Traum, D., Swartout, W., Khooshabeh, P., Kopp, S., Scherer, S., Leuski, A. (eds) Intelligent Virtual Agents. IVA 2016. Lecture Notes in Computer Science(), vol 10011. Springer, Cham. https://doi.org/10.1007/978-3-319-47665-0_58

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  • DOI: https://doi.org/10.1007/978-3-319-47665-0_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47664-3

  • Online ISBN: 978-3-319-47665-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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