We consider model selection for classic Reinforcement Learning (RL) environments – Multi Armed Bandits (MABs) and Markov Decision Processes (MDPs) under general function approximations. In the framework, we do not know classes, denoted by $$\mathcal {F}$$ {M}$$ , where true models reward generating MABs transition kernel MDPs lie, respectively. Instead, are given M nested (hypothesis) classes s...

a characteriation of continuity of the $p$-$lambda$-variation function is given and the helly's selection principle for $lambda bv^{(p)}$ functions is established. a characterization of the inclusion of waterman-shiba classes into classes of functions with given integral modulus of continuity is given. a useful estimate on modulus of variation of functions of class $lambda bv^{(p)}$ is found.

The aim of this work is to investigate the effect of thermal treatment on the grinding behavior of manganese ore in the various size fractions of -1.7+1.18, -1.18+0.6, -0.6+0.3 and -0.3+ 0.15 mm. Breakage Function Determination Software (BFDS) is used to calculate the selection function of the experiment. The results of SEM analysis show the micro-cracks in the thermally treated manganese sampl...

Selecting a set of features which is optimal for a given classiication task is one of the central problems in machine learning. We address the problem using the exible and robust lter technique EUBAFES. EUBAFES is based on a feature weighting approach which computes binary feature weights and therefore a solution in the feature selection sense and also gives detailed information about feature r...

Forecasting road condition after maintenance can help in better road maintenance planning. As road administrations annually collect and store road-related data, data-driven methods can be used in determining forecasting models that result in improved accuracy. In this paper, we compare the prediction models identified by experts and currently used in road administration with simple data-driven ...

Introduction: Mental arithmetic analysis based on Electroencephalogram (EEG) signal for monitoring the state of the user’s brain functioning can be helpful for understanding some psychological disorders such as attention deficit hyperactivity disorder, autism spectrum disorder, or dyscalculia where the difficulty in learning or understanding the arithmetic exists. Most mental arithmetic recogni...

The accuracy-based fitness approach in XCS is one of the most significant changes in comparison with original learning classifier systems. Nonetheless, neither the scaled accuracy function, nor the importance of the relative fitness approach has been investigated in detail. The recent introduction of tournament selection to XCS has shown to make the system more independent from parameter settin...

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