Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps

Mabel Frias; Yaima Filiberto; Gonzalo Nápoles; Rafael Falcon; Rafael Bello; Koen Vanhoof

doi:10.1007/978-3-030-10463-4_7

Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps

Mabel Frias^*, Yaima Filiberto, Gonzalo Nápoles, Rafael Falcon, Rafael Bello, Koen Vanhoof

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Scientific › peer-review

Abstract

Fuzzy Cognitive Maps (FCMs) can be defined as recurrent neural networks that allow modeling complex systems using concepts and causal relations. While this Soft Computing technique has proven to be a valuable knowledge-based tool for building Decision Support Systems, further improvements related to its transparency are still required. In this paper, we focus on designing an FCM-based model where both the causal weights and concepts’ activation values are described by words like low, medium or high. Hybridizing FCMs and the Computing with Words paradigm leads to cognitive models closer to human reasoning, making it more comprehensible for decision makers. The simulations using a well-known case study related to simulation scenarios illustrate the soundness and potential application of the proposed model.

Original language	English
Title of host publication	Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications
Editors	Rafael Bello, Rafael Falcon, José Luis Verdegay
Place of Publication	Cham
Publisher	Springer International Publishing
Pages	127-139
Number of pages	13
ISBN (Print)	978-3-030-10463-4
DOIs	https://doi.org/10.1007/978-3-030-10463-4_7
Publication status	Published - 2019
Externally published	Yes

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10.1007/978-3-030-10463-4_7

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Frias, M., Filiberto, Y., Nápoles, G., Falcon, R., Bello, R., & Vanhoof, K. (2019). Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps. In R. Bello, R. Falcon, & J. L. Verdegay (Eds.), Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications (pp. 127-139). Springer International Publishing. https://doi.org/10.1007/978-3-030-10463-4_7

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title = "Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps",

abstract = "Fuzzy Cognitive Maps (FCMs) can be defined as recurrent neural networks that allow modeling complex systems using concepts and causal relations. While this Soft Computing technique has proven to be a valuable knowledge-based tool for building Decision Support Systems, further improvements related to its transparency are still required. In this paper, we focus on designing an FCM-based model where both the causal weights and concepts{\textquoteright} activation values are described by words like low, medium or high. Hybridizing FCMs and the Computing with Words paradigm leads to cognitive models closer to human reasoning, making it more comprehensible for decision makers. The simulations using a well-known case study related to simulation scenarios illustrate the soundness and potential application of the proposed model.",

author = "Mabel Frias and Yaima Filiberto and Gonzalo N{\'a}poles and Rafael Falcon and Rafael Bello and Koen Vanhoof",

year = "2019",

doi = "10.1007/978-3-030-10463-4_7",

language = "English",

isbn = "978-3-030-10463-4",

pages = "127--139",

editor = "Rafael Bello and Rafael Falcon and Verdegay, {Jos{\'e} Luis}",

booktitle = "Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications",

publisher = "Springer International Publishing",

address = "Switzerland",

}

Frias, M, Filiberto, Y, Nápoles, G, Falcon, R, Bello, R & Vanhoof, K 2019, Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps. in R Bello, R Falcon & JL Verdegay (eds), Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications. Springer International Publishing, Cham, pp. 127-139. https://doi.org/10.1007/978-3-030-10463-4_7

Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps. / Frias, Mabel; Filiberto, Yaima; Nápoles, Gonzalo et al.
Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications. ed. / Rafael Bello; Rafael Falcon; José Luis Verdegay. Cham: Springer International Publishing, 2019. p. 127-139.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Scientific › peer-review

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T1 - Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps

AU - Frias, Mabel

AU - Filiberto, Yaima

AU - Nápoles, Gonzalo

AU - Falcon, Rafael

AU - Bello, Rafael

AU - Vanhoof, Koen

PY - 2019

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N2 - Fuzzy Cognitive Maps (FCMs) can be defined as recurrent neural networks that allow modeling complex systems using concepts and causal relations. While this Soft Computing technique has proven to be a valuable knowledge-based tool for building Decision Support Systems, further improvements related to its transparency are still required. In this paper, we focus on designing an FCM-based model where both the causal weights and concepts’ activation values are described by words like low, medium or high. Hybridizing FCMs and the Computing with Words paradigm leads to cognitive models closer to human reasoning, making it more comprehensible for decision makers. The simulations using a well-known case study related to simulation scenarios illustrate the soundness and potential application of the proposed model.

AB - Fuzzy Cognitive Maps (FCMs) can be defined as recurrent neural networks that allow modeling complex systems using concepts and causal relations. While this Soft Computing technique has proven to be a valuable knowledge-based tool for building Decision Support Systems, further improvements related to its transparency are still required. In this paper, we focus on designing an FCM-based model where both the causal weights and concepts’ activation values are described by words like low, medium or high. Hybridizing FCMs and the Computing with Words paradigm leads to cognitive models closer to human reasoning, making it more comprehensible for decision makers. The simulations using a well-known case study related to simulation scenarios illustrate the soundness and potential application of the proposed model.

U2 - 10.1007/978-3-030-10463-4_7

DO - 10.1007/978-3-030-10463-4_7

M3 - Chapter

SN - 978-3-030-10463-4

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EP - 139

BT - Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications

A2 - Bello, Rafael

A2 - Falcon, Rafael

A2 - Verdegay, José Luis

PB - Springer International Publishing

CY - Cham

ER -

Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps

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