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A review of explanation methods for Bayesian networks
One of the key factors for the acceptance of expert systems in real-world domains is the
ability to explain their reasoning (Buchanan & Shortliffe, 1984; Henrion & Druzdzel, 1990) …
ability to explain their reasoning (Buchanan & Shortliffe, 1984; Henrion & Druzdzel, 1990) …
[كتاب][B] Bayesian artificial intelligence
KB Korb, AE Nicholson - 2010 - books.google.com
The second edition of this bestseller provides a practical and accessible introduction to the
main concepts, foundation, and applications of Bayesian networks. This edition contains a …
main concepts, foundation, and applications of Bayesian networks. This edition contains a …
Aspect-controlled neural argument generation
We rely on arguments in our daily lives to deliver our opinions and base them on evidence,
making them more convincing in turn. However, finding and formulating arguments can be …
making them more convincing in turn. However, finding and formulating arguments can be …
Generating and evaluating evaluative arguments
Evaluative arguments are pervasive in natural human communication. In countless
situations people attempt to advise or persuade their interlocutors that something is …
situations people attempt to advise or persuade their interlocutors that something is …
Natural language processing and user modeling: Synergies and limitations
The fields of user modeling and natural language processing have been closely linked since
the early days of user modeling. Natural language systems consult user models in order to …
the early days of user modeling. Natural language systems consult user models in order to …
The workweek is the best time to start a family–a study of GPT-2 based claim generation
Argument generation is a challenging task whose research is timely considering its potential
impact on social media and the dissemination of information. Here we suggest a pipeline …
impact on social media and the dissemination of information. Here we suggest a pipeline …
BARD: A structured technique for group elicitation of Bayesian networks to support analytic reasoning
In many complex, real‐world situations, problem solving and decision making require
effective reasoning about causation and uncertainty. However, human reasoning in these …
effective reasoning about causation and uncertainty. However, human reasoning in these …
[PDF][PDF] An overview of Amalgam: A machine-learned generation module
We present an overview of Amalgam, a sentence realization module that combines machine-
learned and knowledgeengineered components to produce natural language sentences …
learned and knowledgeengineered components to produce natural language sentences …
Argument and explanation
In this paper, we bring together two closely related, but distinct, notions: argument and
explanation. We clarify their relationship. We then provide an integrative review of relevant …
explanation. We clarify their relationship. We then provide an integrative review of relevant …
A bayesian agent-based framework for argument exchange across networks
In this paper, we introduce a new framework for modelling the exchange of multiple
arguments across agents in a social network. To date, most modelling work concerned with …
arguments across agents in a social network. To date, most modelling work concerned with …