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Titlebook: Algorithmic Decision Theory; 4th International Co Toby Walsh Conference proceedings 2015 Springer International Publishing Switzerland 2015

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發(fā)表于 2025-3-21 19:47:32 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Algorithmic Decision Theory
期刊簡稱4th International Co
影響因子2023Toby Walsh
視頻videohttp://file.papertrans.cn/153/152920/152920.mp4
發(fā)行地址Up-to-date results.Includes supplementary material:
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Algorithmic Decision Theory; 4th International Co Toby Walsh Conference proceedings 2015 Springer International Publishing Switzerland 2015
影響因子This book constitutes the thoroughly refereed conference proceedings of the 4th International Conference on Algorithmic Decision Theory , ADT 2015, held in September 2015 in Lexington, USA. The 32 full papers presented were carefully selected from 76 submissions. The papers are organized in topical sections such as preferences; manipulation, learning and other issues; utility and decision theory; argumentation; bribery and control; social choice; allocation and other problems; doctoral consortium.
Pindex Conference proceedings 2015
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發(fā)表于 2025-3-21 20:48:05 | 只看該作者
Nested Timed Automata with Invariantsropose an alternative definition of P-trees, and formally introduce their compact representation that exploits occurrences of identical subtrees. We show that P-trees generalize lexicographic preference trees and are strictly more expressive. We relate P-trees to answer-set optimization programs and
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Lecture Notes in Computer Sciencey a set of optimal outcomes rather than a single winning outcome. We assume that preferences may be ranked (differ in importance), and we use the Pareto principle adjusted to the case of ranked preferences as the preference aggregation rule. For two important classes of preferences, representing the
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Teng Long,Xingtao Ren,Qing Wang,Chao Wang input multiple partially overlapping datasets with missing data along with expert opinions about the structure of the model and produces an associated directed acyclic graph representing the graphical layer of a Bayesian network. We provide experimental results where we compare our algorithm with a
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發(fā)表于 2025-3-23 01:31:18 | 只看該作者
Teng Long,Xingtao Ren,Qing Wang,Chao Wangation (IVI) has recently been proposed by Weng and Zanuttini (2013). This solving method, which interweaves elicitation and optimization phases, computes a (near) optimal policy without knowing the precise reward values. The procedure as originally presented can be improved in order to reduce the nu
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