Bayesian reinforcement learning with exploration

We consider a general reinforcement learning problem and show that carefully combining the Bayesian optimal policy and an exploring policy leads to minimax sample-complexity bounds in a very general class of (history-based) environments. We also prove lower bounds and show that the new algorithm displays adaptive behaviour when the environment is easier than worst-case

FEATURES OF USING NONSTEROIDAL ANTI-INFLAMMATORY DRUGS IN DENTAL PRACTICE

Aim. This study was conducted to assess the awareness of dentists about the questions of pharmacokinetics and pharmacodynamics of nonsteroidal anti-inflammatory drugs as well as to study the features of their use for the relief of pain syndrome in dental practice.Materials and methods. By means of the questionnaires were studied 107 dentists working in dental clinics and dental departments of General hospitals, especially their use of the nonsteroidal anti-inflammatory drugs for pain relief.Results. It was determined that 85% of doctors use non-selective and moderately selective cyclooxygenase inhibitors (COX), 15%-prefer Cox-2 inhibitor with the pronounced selectivity for pain relief. The highest number of correct answers was given by a group of doctors with work experience from 5 to 10 years (40.3%), the lowest – by doctors with work experience more than 20 years, respectively 40.3% and 36.1% of the total number of doctors from the studied groups.Conclusion. There was noted that it is necessary to pay attention to the peculiarities of pain relief for the improvement of dentists’ work as well as to involve clinical pharmacologists for these purposes

Visualization of trends in subscriber attributes of communities on mobile telecommunications networks

Churn, the decision for a subscriber to leave a provider, is frequently of interest in the telecommunications industry. Previous research provides evidence that social influence can be a factor in mobile telecommunications churn. In our work, presented at ASONAM, we presented a system, called ChurnVis, to visualize the evolution of mobile telecommunications churn and subscriber actions over time. First, we infer a social network from call detail records. Then, we compute components based on an overlay of this social network and churn activity. We compute summaries of the attributes associated with the subscribers and finally, we visualize the components in a privacy preserving way. The system is able to present summaries of thousands of churn components in graphs of hundreds of millions of edges. One of the drawbacks of the original approach was that churn components were sometimes very large, leading to over-aggregation in the summary data. In this extension of the ASONAM paper, we adapt the ChurnVis approach to operate on the output of a community finding algorithm and present new results based on this adaptation.Science Foundation Irelan