The Rice-Shapiro theorem in Computable Topology

We provide requirements on effectively enumerable topological spaces which guarantee that the Rice-Shapiro theorem holds for the computable elements of these spaces. We show that the relaxation of these requirements leads to the classes of effectively enumerable topological spaces where the Rice-Shapiro theorem does not hold. We propose two constructions that generate effectively enumerable topological spaces with particular properties from wn--families and computable trees without computable infinite paths. Using them we propose examples that give a flavor of this class

First Order Theories of Some Lattices of Open Sets

We show that the first order theory of the lattice of open sets in some natural topological spaces is $m$-equivalent to second order arithmetic. We also show that for many natural computable metric spaces and computable domains the first order theory of the lattice of effectively open sets is undecidable. Moreover, for several important spaces (e.g., $\mathbb{R}^n$, $n\geq1$, and the domain $P\omega$) this theory is $m$-equivalent to first order arithmetic

Principles of the Distribution of Productive Forces in the USSR

The work of planning does not end with the drafting and endorsing of a plan. An equally important aspect of this work is to ensure fulfillment of the plan. The means adopted to this end include material and moral incentives and special awards to outstanding enterprises and their workers, the introduction of cost accounting, economically sound prices, the raising of efficiency and profitability and the assimilation and dissemination of the experience of advanced enterprises. At the present stage of development of the Soviet society, the tasks of economic planning have the aim of securing a substantial use in production efficiency so as to bring about a rapid use in the living standards of the soviet people

Accelerating evolutionary algorithms by means of Gaussian processes

Tato práce zkoumá výkon gaussovských procesů (GP) v souvislosti s metodou zvanou Covariance Matrix Adaptation Evolution Strategy (CMA-ES), state-of-the-art v oblasti evoluční optimalizace. Pro měření výkonu byly použity nichingové funkce ze soutěže CEC 2013, které jsou charakteristické vysokým počtem lokálních optim. Práce popisuje integraci CMA-ES a GP jako náhradního modelu a srovnává její výkon s metodou Model Guided Sampling Optimization.This thesis investigates the performance of Gaussian processes (GP) in the context of Covariance Matrix Adaptation Evolution Strategy (CMA-ES), the state-of-the-art evolutionary optimization method for black-box continuous optimization, using niching functions from the CEC 2013 competition, which are characterized by a high number of local optima. It describes the integration of CMA-ES and GP surrogate model and compares its performance to Model Guided Sampling Optimization