Titlebook: Modelling Puzzles in First Order Logic; Adrian Groza Textbook 2021 The Editor(s) (if applicable) and The Author(s), under exclusive licens

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Language in Usetinek & Savukova, .), students in the two undergraduate study programs offered at the Department of English and American Studies at the University of Vienna, Bachelor of Arts (BA) in English and American Studies and Bachelor of Education (BEd) in English, progress to the second module: Language in U

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Multi-objective Job Shop Rescheduling with Estimation of Distribution Algorithme processing time of each operation with the Monte Carlo methods, allocation method is used to decide the operation sequence, and then the expected makespan and total tardiness of each sampling are evaluated. Subsequently, updating mechanism of the probability models is proposed according to the bes

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Seamless Locomotion,ersive, it’s more convincing if the illusion of immersion isn’t constantly being broken in the teleport movements. Seamless locomotion is also commonly referred to as slide movement and rotation. It’s worth noting that this form of locomotion isn’t for everyone. Players who are new to VR or just sen

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Deep Reinforcement Learning for Dynamic Flexible Job-Shop Scheduling with Automated Guided Vehiclesuble deep Q network (D3QN) algorithm to optimize the problem. The evaluation results under nine scenarios demonstrate that the D3QN algorithm has less tardiness than the composite scheduling rules, which indicates that the D3QN algorithm can achieve high-efficiency decision-making in dynamic manufacturing systems.

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Dita ?amánková,Marek Preiss,Tereza P?íhodováleviates the data sparsity problem in the recommendation system. On real data crawled from automobile-related websites, experiments show that the algorithm can obtain more accurate link prediction effects than traditional algorithms.