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Titlebook: Unternehmensdynamik; Horst Albach zum 60. Klaus-Peter Kistner (Lehrstuhl für Betriebswirtsch Book 1991 Betriebswirtschaftlicher Verlag Dr.

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發(fā)表于 2025-3-25 04:07:21 | 只看該作者
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發(fā)表于 2025-3-25 22:39:02 | 只看該作者
Wilhelm Krelle probability distribution over the solution space in a way that ensures convergence to an optimal solution. After introducing the theory and convergence results in a general optimization problem setting, we apply the MRAS approach to various MDP settings. For the finite- and infinite-horizon setting
26#
發(fā)表于 2025-3-26 03:40:14 | 只看該作者
ns in social dilemmas. The model is embedded into a computerized version of such a conflict. It reflects the interplay between motives and knowledge for the generation of actions. Ecological and social knowledge are modeled. Action knowledge is represented in form of action schemata. Intention forma
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發(fā)表于 2025-3-26 07:05:25 | 只看該作者
Klaus Brockhoffecessary inputs are provided. However, a basic understanding of FEA theory can make this black box much easier to use. This chapter is a concise summary and description of the Finite Element Analysis theory. It will introduce and discuss the fundamental concepts of FEA theory to help in understandin
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發(fā)表于 2025-3-26 09:01:41 | 只看該作者
Wolfram Fischerhe term usability will be defined at the beginning of Sect.?.. Then, the same section presents the fundamentals of traditional usability evaluation methods and of methods for automatic usability evaluation. This will show the high efforts of the traditional evaluation methods and the advantages of t
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發(fā)表于 2025-3-26 16:43:03 | 只看該作者
Gerhard Menscharameters of the structure of interest with a relatively small extra computational cost (El Sabbagh et al. 2006). In electromagnetic simulations, the process of obtaining the derivatives may not require additional simulations to the simulation for obtaining the figures of merit (El Sabbagh et al. 20
30#
發(fā)表于 2025-3-26 17:22:13 | 只看該作者
Joachim Schwalbachble with Markov decision processes.Rigorous theoretical deri.Often, real-world problems modeled by Markov decision processes (MDPs) are difficult to solve in practise because of the curse of dimensionality. In others, explicit specification of the MDP model parameters is not feasible, but simulation
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