Cosmin Bonchis

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In this paper we present WebPS, an open-source web-enabled simulator for P systems, and a P accelerator for parallelization of the existing sequential simulators. The simulator is based on CLIPS, and it is already available as a web application. The P accelerator is used to parallelize the existing sequential simulators of the P systems. We exemplify this(More)
We propose a parametric family of measures of fairness in allocations of TU-cooperative games. Their definition is based on generalized Rényi Entropy, is related to the Cowell-Kuga generalized entropy indices in welfare economics, and aims to parallel the spirit of the notion of price of anarchy in the case of convex TU-cooperative games. Since computing(More)
" The words, the sad words, Sometimes surround the time As a pipe, the water which flows within. " Nichita St˘ anescu Summary. Starting from Shannon theory of information, we present the case of producing information in the form of multisets, and encoding information using multisets. We compute the entropy of a multiset information source by constructing an(More)
We investigate partitioning of integer sequences into heapable subsequences (previously defined and established by Mitzenmacher et al. [BHMZ11]). We show that an extension of patience sorting computes the decomposition into a minimal number of heapable subsequences (MHS). We connect this parameter to an interactive particle system, a multiset extension of(More)
We study minimum entropy submodular optimization, a common generalization of the minimum entropy set cover problem, studied earlier by Cardinal et al., and the submodular set cover problem (Wolsey [Wol82], Fujishige [BIKP01], etc). We give a general bound of the approximation performance of the greedy algorithm using an approach that can be interpreted in(More)
We study the approximability of instances of the minimum entropy set cover problem, parameterized by the average frequency of a random element in the covering sets. We analyze an algorithm combining a greedy approach with another one biased towards large sets. The algorithm is controled by the percentage of elements to which we apply the biased approach.(More)