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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

A Framework for Measuring Information Asymmetry

February 1, 2023

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Authors

Yakoub Salhi

CRIL


DOI:

10.1609/aaai.v34i03.5691


Abstract:

Information asymmetry occurs when an imbalance of knowledge exists between two parties, such as a buyer and a seller, a regulator and an operator, and an employer and an employee. It is a key concept in several domains, in particular, in economics. We propose in this work a general logic-based framework for measuring the information asymmetry between two parties. A situation of information asymmetry is represented by a knowledge base and a set of questions. We define the notion of information asymmetry measure through rationality postulates. We further introduce a syntactic concept, called minimal question subset (MQS), to take into consideration the fact that answering some questions allows avoiding others. This concept is used for defining rationality postulates and measures. Finally, we propose a method for computing the MQSes of a given situation of information asymmetry.

Topics: AAAI

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Yakoub Salhi A Framework for Measuring Information Asymmetry Proceedings of the AAAI Conference on Artificial Intelligence (2020) 2983-2990.

Yakoub Salhi A Framework for Measuring Information Asymmetry AAAI 2020, 2983-2990.

Yakoub Salhi (2020). A Framework for Measuring Information Asymmetry. Proceedings of the AAAI Conference on Artificial Intelligence, 2983-2990.

Yakoub Salhi. A Framework for Measuring Information Asymmetry. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.2983-2990.

Yakoub Salhi. 2020. A Framework for Measuring Information Asymmetry. "Proceedings of the AAAI Conference on Artificial Intelligence". 2983-2990.

Yakoub Salhi. (2020) "A Framework for Measuring Information Asymmetry", Proceedings of the AAAI Conference on Artificial Intelligence, p.2983-2990

Yakoub Salhi, "A Framework for Measuring Information Asymmetry", AAAI, p.2983-2990, 2020.

Yakoub Salhi. "A Framework for Measuring Information Asymmetry". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.2983-2990.

Yakoub Salhi. "A Framework for Measuring Information Asymmetry". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 2983-2990.

Yakoub Salhi. A Framework for Measuring Information Asymmetry. AAAI[Internet]. 2020[cited 2023]; 2983-2990.


ISSN: 2374-3468


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