隼鹰 发表于 2025-3-25 06:59:43

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arrhythmic 发表于 2025-3-25 10:11:55

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Lumbar-Spine 发表于 2025-3-25 13:28:28

0166-6991 l life court cases, results of experimental research, and in.Relevant to, and drawing from, a range of disciplines, the chapters in this collection show the diversity, and applicability, of research in Bayesian argumentation. Together, they form a challenge to philosophers versed in both the use and

相同 发表于 2025-3-25 16:20:33

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朴素 发表于 2025-3-25 22:07:30

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mortuary 发表于 2025-3-26 03:08:12

A Survey of Uncertainties and Their Consequences in Probabilistic Legal Argumentationalistic example. After introducing the Carneades argument model and its probabilistic semantics, we propose an extension to the Carneades Bayesian Network model to support probability distributions over argument weights, a feature we believe is desirable. Finally, we scout possible future approaches to facilitate reasoning with argument weights.

Ornithologist 发表于 2025-3-26 06:50:43

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Allowance 发表于 2025-3-26 10:42:06

Human Brain and Artificial IntelligenceThe main aim of this chapter is to investigate which assumptions of the standard theory we have to give up to account for our communicative behavior, when preferences between partners are not aligned.

fructose 发表于 2025-3-26 13:43:42

Ziyu Zhao,Hui Shen,Dewen Hu,Kerang Zhangmposes a deductive relation. I argue for the second class, as the first class is problematic if the arguments involve conditionals. I present a measure of argument strength that allows for dealing explicitly with uncertain conditionals in the premise set.

平淡而无味 发表于 2025-3-26 17:39:50

Masumi Inaba M.D.,Yoshikata Inaba M.D., Cambridge, 2008). This chapter treats this issue from the perspective of the Bayesian approach to argument (Hahn & Oaksford, Psychol Rev 114:704–732, 2007a; Hahn et al., Informal Log 29:337–367, 2009) and summarises empirical evidence on key intuitions.
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查看完整版本: Titlebook: Bayesian Argumentation; The practical side o Frank Zenker Book 2013 Springer Science+Business Media Dordrecht 2013 Ad Hominem Argument Baye