Exploration vs Exploitation vs Safety: Risk-averse Multi-Armed Bandits

Motivated by applications in energy management, this paper presents the Multi-Armed Risk-Aware Bandit (MARAB) algorithm. With the goal of limiting the exploration of risky arms, MARAB takes as arm quality its conditional value at risk. When the user-supplied risk level goes to 0, the arm quality tends toward the essential infimum of the arm distribution density, and MARAB tends toward the MIN multi-armed bandit algorithm, aimed at the arm with maximal minimal value. As a first contribution, this paper presents a theoretical analysis of the MIN algorithm under mild assumptions, establishing its robustness comparatively to UCB. The analysis is supported by extensive experimental validation of MIN and MARAB compared to UCB and state-of-art risk-aware MAB algorithms on artificial and real-world problems.Comment: 16 page

Response-surface-model-based system sizing for nearly/net zero energy buildings under uncertainty

Properly treating uncertainty is critical for robust system sizing of nearly/net zero energy buildings (ZEBs). To treat uncertainty, the conventional method conducts Monte Carlo simulations for thousands of possible design options, which inevitably leads to computation load that is heavy or even impossible to handle. In order to reduce the number of Monte Carlo simulations, this study proposes a response-surface-model-based system sizing method. The response surface models of design criteria (i.e., the annual energy match ratio, self-consumption ratio and initial investment) are established based on Monte Carlo simulations for 29 specific design points which are determined by Box-Behnken design. With the response surface models, the overall performances (i.e., the weighted performance of the design criteria) of all design options (i.e., sizing combinations of photovoltaic, wind turbine and electric storage) are evaluated, and the design option with the maximal overall performance is finally selected. Cases studies with 1331 design options have validated the proposed method for 10,000 randomly produced decision scenarios (i.e., users’ preferences to the design criteria). The results show that the established response surface models reasonably predict the design criteria with errors no greater than 3.5% at a cumulative probability of 95%. The proposed method reduces the number of Monte Carlos simulations by 97.8%, and robustly sorts out top 1.1% design options in expectation. With the largely reduced Monte Carlo simulations and high overall performance of the selected design option, the proposed method provides a practical and efficient means for system sizing of nearly/net ZEBs under uncertainty

Measuring voting power in convex policy spaces

Classical power index analysis considers the individual's ability to influence the aggregated group decision by changing its own vote, where all decisions and votes are assumed to be binary. In many practical applications we have more options than either "yes" or "no". Here we generalize three important power indices to continuous convex policy spaces. This allows the analysis of a collection of economic problems like e.g. tax rates or spending that otherwise would not be covered in binary models.Comment: 31 pages, 9 table

The Bacterial Chemotactic Response Reflects a Compromise Between Transient and Steady State Behavior

Swimming bacteria detect chemical gradients by performing temporal comparisons of recent measurements of chemical concentration. These comparisons are described quantitatively by the chemotactic response function, which we expect to optimize chemotactic behavioral performance. We identify two independent chemotactic performance criteria: in the short run, a favorable response function should move bacteria up chemoattractant gradients, while in the long run, bacteria should aggregate at peaks of chemoattractant concentration. Surprisingly, these two criteria conflict, so that when one performance criterion is most favorable, the other is unfavorable. Since both types of behavior are biologically relevant, we include both behaviors in a composite optimization that yields a response function that closely resembles experimental measurements. Our work suggests that the bacterial chemotactic response function can be derived from simple behavioral considerations, and sheds light on how the response function contributes to chemotactic performance.Comment: 19 pages, 5 figure

Reactor Neutrino Flux Uncertainty Suppression on Multiple Detector Experiments

This publication provides a coherent treatment for the reactor neutrino flux uncertainties suppression, specially focussed on the latest $\theta_{13}$ measurement. The treatment starts with single detector in single reactor site, most relevant for all reactor experiments beyond $\theta_{13}$. We demonstrate there is no trivial error cancellation, thus the flux systematic error can remain dominant even after the adoption of multi-detector configurations. However, three mechanisms for flux error suppression have been identified and calculated in the context of Double Chooz, Daya Bay and RENO sites. Our analysis computes the error {\it suppression fraction} using simplified scenarios to maximise relative comparison among experiments. We have validated the only mechanism exploited so far by experiments to improve the precision of the published $\theta_{13}$. The other two newly identified mechanisms could lead to total error flux cancellation under specific conditions and are expected to have major implications on the global $\theta_{13}$ knowledge today. First, Double Chooz, in its final configuration, is the only experiment benefiting from a negligible reactor flux error due to a $\sim$90\% geometrical suppression. Second, Daya Bay and RENO could benefit from their partial geometrical cancellation, yielding a potential $\sim$50\% error suppression, thus significantly improving the global $\theta_{13}$ precision today. And third, we illustrate the rationale behind further error suppression upon the exploitation of the inter-reactor error correlations, so far neglected. So, our publication is a key step forward in the context of high precision neutrino reactor experiments providing insight on the suppression of their intrinsic flux error uncertainty, thus affecting past and current experimental results, as well as the design of future experiments