The model of incomplete cooperative games incorporates uncertainty into the classical model of cooperative games by considering a partial characteristic function. Thus the values for some of the coalitions are not kno...
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The model of incomplete cooperative games incorporates uncertainty into the classical model of cooperative games by considering a partial characteristic function. Thus the values for some of the coalitions are not known. The main focus of this paper is the class of 1-convex cooperative games under this framework. We are interested in two heavily intertwined questions. First, given an incomplete game, in which ways can we fill in the missing values to obtain a classical 1-convex game? Such complete games are called 1-convex extensions. For the class of minimal incomplete games (in which precisely the values of singletons and grand coalitions are known), we provide an answer in terms of a description of the set of 1-convex extensions. The description employs extreme points and extreme rays of the set. We also provide bounds on sets of 1-convex extensions for such games. Second, how to determine in a rational, fair, and efficient way the payoffs of players based only on the known values of coalitions? Based on the description of the set of 1-convex extensions, we introduce generalisations of three solution concepts (values) for complete games, namely the τ-value, the Shapley value and the nucleolus. We consider two variants where we compute the centre of gravity of either extreme games or of a combination of extreme games and extreme rays. We show that all of the generalised values coincide for minimal incomplete games which allows to introduce the average value. For this value, we provide three different axiomatisations based on axiomatic characterisations of the τ-value and the Shapley value for classical cooperative games. Finally, we turn our attention to incomplete games with defined upper vector, asking the same questions and this time arriving to different conclusions. This provides a benchmark to test our tools and knowledge of the average value. This part highlights the importance and also the difficulty of considering more general classes of incomplete games.
The cutwidth problem is to find a linear layout of a network so that the maximal number of cuts (cw) of a line separating consecutive vertices is minimized. A related and more natural problem is the cyclic cutwidth (c...
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Multilevel Monte Carlo (MLMC) has become an important methodology in appliedmathematics for reducing the computational cost of weak approximations. For many problems, it is well-known that strong pairwise coupling of...
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Let Y = { Y t :t ≥ 0} be a semi‐Markov process with finite state space S. Assume that Y is either irreducible and S is then partitioned into two classes A and B , or, that Y is absorbing and S is partitioned into A ...
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Let Y = { Y t :t ≥ 0} be a semi‐Markov process with finite state space S. Assume that Y is either irreducible and S is then partitioned into two classes A and B , or, that Y is absorbing and S is partitioned into A , B and C , where C is the set of all absorbing states of Y. Denote by T A, m ( t ) the m th sojourn time of Y in A during [0, t ]. T A, m ( t ) is thus defined as the duration in [0, t ] of the m th visit of Y to A if A is visited by Y during [0, t ] at least m times; T A, m ( t ) = 0 otherwise. We derive a recurrence relation for the vectors of double Laplace transforms g m **( T 1 , T 2 ) = { g m **( T 1 , T 2 ; S ): s S C }, m = 1,2,… which are defined by with T 1 , T 2 , Re( T 1 ), Re( T 2 ) > 0. This result is then applied to alternating renewal processes. Symbolic Laplace transform inversion with MAPLE is used to obtain the first two moments of T A, m ( t ). The assumed holding time distributions are exponential and Erlang respectively. This paper is a continuation of some of the author's recent work on the distribution theory of sojourn times in a subset of the finite state space of a (semi‐)Markov process where the time horizon t = + ∞. The practical importance of considering a finite time horizon for semi‐Markov reliability models has been discussed recently by Jack (1991), Jack and Dagpunar (1992), and Christer and Jack (1991).
Blockchain offers the opportunity to use the transaction graph for financial governance, yet properties of this graph are understudied. One key question in this direction is the extent to which the transaction graph c...
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Dynamic and flexible operation of a carbon capture plant is important as thermal power plants must be operated very flexibly to accommodate large shares of intermittent energy sources such as wind and solar energy. To...
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Dynamic and flexible operation of a carbon capture plant is important as thermal power plants must be operated very flexibly to accommodate large shares of intermittent energy sources such as wind and solar energy. To facilitate such operation, dynamic models for simulation, optimization and control system design are crucial. In this paper, we present a dynamic mathematical model for the absorption and desorption columns in a carbon capture plant. Moreover, we implement a decentralized proportional-integral (PI) based control scheme and we evaluate the performance of the control structure for various operational procedures, e.g. start-up, load changes, noise on the flue gas flow rate and composition. Note that the carbon capture plant is based on the solvent storage configuration. To the authors knowledge, this is the first paper addressing the issue of start-up operation and control of carbon capture. The study demonstrates that the implemented control structure keeps the carbon capture process at 90% CO 2 removal rate with a deviation up to 8% during load variations. In addition, it reveals that the control structure brings the process to the desired set point in approximately 10 min during process start-up.
Within the area of multi-Agent systems, normative systems are a widely used framework for the coordination of interdependent activities. A crucial problem associated with normative systems is that of synthesising norm...
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Cloud-based applications are composed of services offered by distinct third-party cloud providers. The selection of the proper cloud services that fit the application needs is based on cloud-related information, i.e. ...
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Bitcoin is the leading cryptocurrency with the highest market value among digital currencies. Therefore, predicting the value of Bitcoin can help to understand the entire cryptocurrency market. However, Bitcoin has ha...
Bitcoin is the leading cryptocurrency with the highest market value among digital currencies. Therefore, predicting the value of Bitcoin can help to understand the entire cryptocurrency market. However, Bitcoin has had a lot of price fluctuations since its inception. In this paper, we are going to forecast the price of Bitcoin using news headline analysis, technical analysis indicators, and historical financial data. The news headlines used in this article are scraped from the Cointelegraph news website, which contains 3988 news headlines related to Bitcoin between 2/7/2020 and 3/8/2021. A transformer pre-trained model on cryptocurrency-related texts called CryptoBERT, which is a BERT-based sentiment analysis model, has been used to analyze the textual data. Also, a novel hybrid 2DCNN-GRU deep learning model has been used to predict the price. To adjust the parameters of this model, a parameter tuning method based on orthogonal arrays called the Taguchi method has been employed. Finally, to examine the proposed model’s efficiency, the obtained results have been compared with other deep learning models from the literature review that used text data to predict bitcoin prices. The results show that this model outperformed other models in terms of MAE criterion, while in the other three criteria, namely MSE, RMSE and MAPE, it still demonstrated good results.
The JAERI quantum molecular dynamics (JQMD) model has been successfully used for a long time now to describe many different aspects of nuclear reactions in a unified way. In some cases, however, the JQMD model cannot ...
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The JAERI quantum molecular dynamics (JQMD) model has been successfully used for a long time now to describe many different aspects of nuclear reactions in a unified way. In some cases, however, the JQMD model cannot produce consistent results: First, it lacks a fully relativistically covariant approach to the problem of molecular dynamics; second, the quantum-mechanical ground state of nuclei cannot be faithfully reproduced in a semiclassical framework. Therefore, we introduce R-JQMD, an improved version of JQMD that also features a new ground-state initialization algorithm for nuclei. We compare the structure of the two codes and discuss whether R-JQMD can be adjusted to improve JQMD's agreement with measured heavy-ion fragmentation cross sections.
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