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Exact Learning from Membership Queries: Some Techniques, Results and New Directions

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Algorithmic Learning Theory (ALT 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8139))

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Abstract

Given a black box that contains a function f:D → R from some class of functions C. The black box can receive an element d (query) of the domain D and in time T returns the value f(d) ∈ R. Our goal is to exactly find (exactly learn) f with minimum number of queries and optimal time complexity. Or at least decide whether f ≡ g for some function g ∈ C.

This problem has different names in different areas: Interpolation, Exactly Learning, Inferring, Identifying, Active Learning, Guessing Game, Testing, Functional Verification, Hitting Set and Black Box PIT from Substitution or Membership Queries.

In this survey we give some of the results known from the literature, different techniques used mainly for the problem of exact learning and new directions that we think are worth investigating.

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  1. Technion, Haifa, Israel

    Nader H. Bshouty

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  1. Nader H. Bshouty
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  1. National University of Singapore, Republic of Singapore

    Sanjay Jain  & Frank Stephan  & 

  2. Inria Lille - Nord Europe, Villeneuve d’Ascq, France

    Rémi Munos

  3. Hokkaido University, Sapporo, Japan

    Thomas Zeugmann

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Bshouty, N.H. (2013). Exact Learning from Membership Queries: Some Techniques, Results and New Directions. In: Jain, S., Munos, R., Stephan, F., Zeugmann, T. (eds) Algorithmic Learning Theory. ALT 2013. Lecture Notes in Computer Science(), vol 8139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40935-6_4

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