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Comparing Humans and AI Agents

  • Javier Insa-Cabrera
  • David L. Dowe
  • Sergio España-Cubillo
  • M. Victoria Hernández-Lloreda
  • José Hernández-Orallo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6830)

Abstract

Comparing humans and machines is one important source of information about both machine and human strengths and limitations. Most of these comparisons and competitions are performed in rather specific tasks such as calculus, speech recognition, translation, games, etc. The information conveyed by these experiments is limited, since it portrays that machines are much better than humans at some domains and worse at others. In fact, CAPTCHAs exploit this fact. However, there have only been a few proposals of general intelligence tests in the last two decades, and, to our knowledge, just a couple of implementations and evaluations. In this paper, we implement one of the most recent test proposals, devise an interface for humans and use it to compare the intelligence of humans and Q-learning, a popular reinforcement learning algorithm. The results are highly informative in many ways, raising many questions on the use of a (universal) distribution of environments, on the role of measuring knowledge acquisition, and other issues, such as speed, duration of the test, scalability, etc.

Keywords

Intelligence measurement universal intelligence general vs specific intelligence reinforcement learning IQ tests 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Javier Insa-Cabrera
    • 1
  • David L. Dowe
    • 2
  • Sergio España-Cubillo
    • 3
  • M. Victoria Hernández-Lloreda
    • 4
  • José Hernández-Orallo
    • 1
  1. 1.DSICUniversitat Politècnica de ValènciaSpain
  2. 2.Clayton School of Information TechnologyMonash UniversityAustralia
  3. 3.ProS Research CenterUniversitat Politècnica de ValènciaSpain
  4. 4.Departamento de Metodología de las Ciencias del ComportamientoUniversidad Complutense de MadridSpain

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