A Graph-based Similarity Function for CBDT: Acquiring and Using New Information

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Tác giả: Federico E Contiggiani, Fernando Delbianco, Fernando Tohmé

Ngôn ngữ: eng

Ký hiệu phân loại: 513.17 Arithmetic

Thông tin xuất bản: 2021

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 166850

Comment: 26 pages, 4 figuresOne of the consequences of persistent technological change is that it force individuals to make decisions under extreme uncertainty. This means that traditional decision-making frameworks cannot be applied. To address this issue we introduce a variant of Case-Based Decision Theory, in which the solution to a problem obtains in terms of the distance to previous problems. We formalize this by defining a space based on an orthogonal basis of features of problems. We show how this framework evolves upon the acquisition of new information, namely features or values of them arising in new problems. We discuss how this can be useful to evaluate decisions based on not yet existing data.
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