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Titlebook: Algorithmic Decision Theory; 8th International Co Rupert Freeman,Nicholas Mattei Conference proceedings 2025 The Editor(s) (if applicable)

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發(fā)表于 2025-3-21 18:16:18 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Algorithmic Decision Theory
期刊簡稱8th International Co
影響因子2023Rupert Freeman,Nicholas Mattei
視頻videohttp://file.papertrans.cn/168/167383/167383.mp4
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Algorithmic Decision Theory; 8th International Co Rupert Freeman,Nicholas Mattei Conference proceedings 2025 The Editor(s) (if applicable)
影響因子.This book constitutes the conference proceedings of the 8th International Conference on Algorithmic Decision Theory, ADT 2024, held in New Brunswick, NJ, USA, during October 14-16, 2024...The 18 full papers and 8 one-page abstracts presented were carefully selected from 39 submissions.?The papers cover most of the major aspects of algorithmic decision theory, such as preference modeling and elicitation, voting, preference aggregation, fair division and resource allocation, coalition formation, game theory, and matching..?.
Pindex Conference proceedings 2025
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發(fā)表于 2025-3-21 21:35:20 | 只看該作者
Protective and?Nonprotective Subset Sum Games: A Parameterized Complexity Analysise, and the number of different numbers in the input on the complexity of the problem. Second, we consider a further variant of the game, called ., where?Player?. additionally has the goal that Player?. reaches a value of at least?..?In a nutshell, we show that most algorithms for the nonprotective v
板凳
發(fā)表于 2025-3-22 00:45:10 | 只看該作者
Non-maximizing Policies that?Fulfill Multi-criterion Aspirations in?Expectationof the evaluation metrics falls into some given convex set, called the aspiration set. Our algorithm guarantees that this task is fulfilled by using simplices to approximate feasibility sets and propagate aspirations forward while ensuring they remain feasible. It has complexity linear in the number
地板
發(fā)表于 2025-3-22 04:38:34 | 只看該作者
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發(fā)表于 2025-3-22 11:25:34 | 只看該作者
Collaborative Information Dissemination with?Graph-Based Multi-Agent Reinforcement Learningmplish cooperative information dissemination, L-DyAN?and HL-DyAN, differing in terms of the information exchanged?among agents. Our experimental results show that our trained policies outperform existing methods, including the state-of-the-art heuristic, in terms of network coverage and communicatio
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發(fā)表于 2025-3-22 13:55:29 | 只看該作者
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發(fā)表于 2025-3-22 19:45:44 | 只看該作者
Learning Multiple Multicriteria Additive Models from?Heterogeneous Preferencesming based resolution approach to solve?this . problem (PLS). We?also propose a heuristic to deal with large datasets. We study?the performance of both algorithms through experiments using synthetic and?real data.
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發(fā)表于 2025-3-23 03:57:55 | 只看該作者
F. J. Leonberger,J. P. Donnellynvergence. The pursuit of a polynomial-time algorithm for SSGs is an active area of research. This paper?is intended to support such research by making it easier to study?the graphical structure of SSGs. Our contributions are: (1) a generating algorithm for Stopping Games, (2) a proof that the algor
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發(fā)表于 2025-3-23 07:14:30 | 只看該作者
https://doi.org/10.1007/978-3-642-97074-0e, and the number of different numbers in the input on the complexity of the problem. Second, we consider a further variant of the game, called ., where?Player?. additionally has the goal that Player?. reaches a value of at least?..?In a nutshell, we show that most algorithms for the nonprotective v
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