Titlebook: Limits of Computation; From a Programming P Bernhard Reus Textbook 2016 The Editor(s) (if applicable) and The Author(s), under exclusive li

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Bernhard Reusnd accuracy”, rarely all satisfied by existing interpretable methods. The structure and stability of random forests make them good candidates to improve the performance of interpretable algorithms. The first part of this chapter focuses on rule learning models, which are simple and highly predictive

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Problems and Effective Procedures term “effective procedure” is introduced that describes a program executable in a finite number of simple steps in a mechanical way. Sets and structures on sets, i.e. relations and functions, together with their basic operations, are defined and some basic reasoning principles reviewed.

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Programs as Data Objectslers, interpreters, and specialisers, which are briefly explained in this chapter. In order to be able to write such programs in ., we need to be able to treat other .-programs as data. To achieve that, an encoding for abstract syntax trees of .-programs as lists is presented. Such lists can in turn

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An Undecidable (Non-computable) Problemis undecidable i.e. that no computer program can solve. We define the concept of .-decidability and define the famous Halting problem whether a given .-program terminates when run on a given input. The concept of diagonalisation is explained and then used to prove that the Halting problem is .-undec

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