Intrinsically motivated information foraging

Ian Fasel, Andrew Wilt, Nassim Mafi, Clayton T. Morrison

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

We treat information gathering as a POMDP in which the goal is to maximize an accumulated intrinsic reward at each time step based on the negative entropy of the agent's beliefs about the world state. We show that such information foraging agents can discover intelligent exploration policies that take into account the long-term effects of sensor and motor actions, and can automatically adapt to variations in sensor noise, different amounts of prior information, and limited memory conditions.

Original languageEnglish (US)
Title of host publication2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Conference Program
Pages101-107
Number of pages7
DOIs
StatePublished - Nov 12 2010
Event2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Ann Arbor, MI, United States
Duration: Aug 18 2010Aug 21 2010

Publication series

Name2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Conference Program

Other

Other2010 IEEE 9th International Conference on Development and Learning, ICDL-2010
CountryUnited States
CityAnn Arbor, MI
Period8/18/108/21/10

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Software
  • Education

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  • Cite this

    Fasel, I., Wilt, A., Mafi, N., & Morrison, C. T. (2010). Intrinsically motivated information foraging. In 2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Conference Program (pp. 101-107). [5578859] (2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Conference Program). https://doi.org/10.1109/DEVLRN.2010.5578859