Publication:
Using Boolean Functions of context factors for adaptive mental model aggregation in organisational learning

Placeholder

Departments

School / College / Institute

Program

KU Authors

Co-Authors

Treur, Jan

Publication Date

Language

Embargo Status

Journal Title

Journal ISSN

Volume Title

Alternative Title

Abstract

Aggregation of individual mental models to obtain shared mental models for an organization is a crucial process for organizational learning. This aggregation process usually depends on several context factors that may vary over circumstances. It is explored how Boolean functions of these context factors can be used to model this form of adaptation. For adaptation of aggregation of mental model connections (represented by first-order self-model states), a second-order adaptive self-modeling network model for organizational learning was designed. It is shown how in such a network model, Boolean functions can be used to express logical combinations of context factors and based on this can exert context-sensitive control over the mental model aggregation process.

Source

Publisher

Springer International Publishing AG

Subject

Computer science, Artificial intelligence, Theory methods

Citation

Has Part

Source

Biologically Inspired Cognitive Architectures 2021

Book Series Title

Edition

DOI

10.1007/978-3-030-96993-6_5

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

0

Views

0

Downloads

View PlumX Details