Probabilistic Recursion Theory and Implicit Computational Complexity

نویسنده

  • Sara Zuppiroli
چکیده

In this thesis we provide a characterization of probabilistic computation in itself, from a recursion-theoretical perspective, without reducing it to deterministic computation. More specifically, we show that probabilistic computable functions, i.e., those functions which are computed by Probabilistic Turing Machines (PTM), can be characterized by a natural generalization of Kleene’s partial recursive functions which includes, among initial functions, one that returns identity or successor with probability 1 2 . We then prove the equiexpressivity of the obtained algebra and the class of functions computed by PTMs. In the the second part of the thesis we investigate the relations existing between our recursiontheoretical framework and sub-recursive classes, in the spirit of Implicit Computational Complexity. More precisely, endowing predicative recurrence with a random base function is proved to lead to a characterization of polynomial-time computable probabilistic functions.

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تاریخ انتشار 2014