eagle-i Oregon Health & Science UniversityOregon Health & Science University
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Learning Mixed-Initiative Dialogue Strategies

eagle-i ID


Resource Type

  1. Software


  1. Resource Description
    "The software from this research project enables next generation dialogue systems to be able to collaborate with a user without the limitations of system-initiative interaction in order to solve complex tasks in an optimal manner. The research develops reinforcement learning (RL) strategies to learn dialogue policies that are mixed-initiative. The specific aims of this are to (a) extend RL to mixed-initiative dialogue interaction; (b) allow the system policy to adapt to different user types, such as people with poor memory, or poor problem-solving skills; and (c) simultaneously learn the policy for the simulated user. This approach will allow more advanced dialogue systems to be deployed, such as assisting the elderly so they can live independently longer, and helping provide health care information to rural areas. The proposed research project will result in a toolkit that will allow a wide range of users to easily develop dialogue policies. The toolkit will (a) allow students to be effectively trained in this area, (b) lower the barrier for other researchers to contribute to the field, and (c) help transfer this new technology to industry."
  2. Used by
    Center for Spoken Language Understanding
  3. Website(s)
  4. Website(s)
  5. Software license
    Open source software license
Provenance Metadata About This Resource Record
Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016