Eric Allender;Harry Buhrman;Luke Friedman;Bruno Loff
This paper is motivated by a conjecture that BPP can be characterized in
terms of polynomial-time nonadaptive reductions to the set of Kolmogorov-random
strings. In this paper we show that an approach laid out in [Allender et al] to
settle this conjecture cannot succeed without significant alteration, but that
it does bear fruit if we consider time-bounded Kolmogorov complexity instead.
We show that if a set A is reducible in polynomial time to the set of
time-t-bounded Kolmogorov random strings (for all large enough time bounds t),
then A is in P/poly, and that if in addition such a reduction exists for any
universal Turing machine one uses in the definition of Kolmogorov complexity,
then A is in PSPACE.
AF: Medium: Computational Complexity Theory and Circuit Complexity; Funder: National Science Foundation; Code: 1064785
A POST´S PROGRAM FOR COMPLEXITY THEORY; Funder: National Science Foundation; Code: SFRH/BD/43169/2008
Collaborative Research: Understanding, Coping with, and Benefiting from, Intractability; Funder: National Science Foundation; Code: 0832787
Bibliographic References
4 Documents citing this article
Shuichi Hirahara;Akitoshi Kawamura, 2017, On characterizations of randomized computation using plain Kolmogorov complexity1, Computability, 7, 1, pp. 45-56, 10.3233/com-170075.
Eric Allender, Lecture notes in computer science, The Complexity of Complexity, pp. 79-94, 2016, 10.1007/978-3-319-50062-1_6.
Shuichi Hirahara;Akitoshi Kawamura, Lecture notes in computer science, On Characterizations of Randomized Computation Using Plain Kolmogorov Complexity, pp. 348-359, 2014, 10.1007/978-3-662-44465-8_30.