A Modeling Environment for Reified Temporal-Causal Networks: Modeling Plasticity and Metaplasticity in Cognitive Agent Models

Jan Treur

doi:10.1007/978-3-030-33792-6_33

A Modeling Environment for Reified Temporal-Causal Networks: Modeling Plasticity and Metaplasticity in Cognitive Agent Models

Jan Treur^*

^*Corresponding author for this work

Computer Science

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

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Abstract

Plasticity is a crucial adaptive characteristic of the brain. Relatively recently mechanisms have been found showing that plasticity itself is controlled by what is called metaplasticity. In this paper a modeling environment is introduced to develop and simulate reified temporal-causal network models that can be applied for cognitive agent models. It is shown how this environment is a useful tool to model plasticity combined with metaplasticity.

Original language	English
Title of host publication	PRIMA 2019: Principles and Practice of Multi-Agent Systems
Subtitle of host publication	22nd International Conference, Turin, Italy, October 28–31, 2019, Proceedings
Editors	Matteo Baldoni, Mehdi Dastani, Beishui Liao, Yuko Sakurai, Rym Zalila Wenkstern
Publisher	Springer
Pages	487-495
Number of pages	9
ISBN (Electronic)	9783030337926
ISBN (Print)	9783030337919
DOIs	https://doi.org/10.1007/978-3-030-33792-6_33
Publication status	Published - 2019
Event	22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019 - Turin, Italy Duration: 28 Oct 2019 → 31 Oct 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11873 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019
Country/Territory	Italy
City	Turin
Period	28/10/19 → 31/10/19

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10.1007/978-3-030-33792-6_33

Treur2019_Chapter_AModelingEnvironmentForReifiedFinal published version, 789 KBLicence: Article 25fa Dutch Copyright Act

https://www.researchgate.net/publication/335473145

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Treur, J. (2019). A Modeling Environment for Reified Temporal-Causal Networks: Modeling Plasticity and Metaplasticity in Cognitive Agent Models. In M. Baldoni, M. Dastani, B. Liao, Y. Sakurai, & R. Zalila Wenkstern (Eds.), PRIMA 2019: Principles and Practice of Multi-Agent Systems: 22nd International Conference, Turin, Italy, October 28–31, 2019, Proceedings (pp. 487-495). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11873 LNAI). Springer. https://doi.org/10.1007/978-3-030-33792-6_33

Treur, Jan. / A Modeling Environment for Reified Temporal-Causal Networks : Modeling Plasticity and Metaplasticity in Cognitive Agent Models. PRIMA 2019: Principles and Practice of Multi-Agent Systems: 22nd International Conference, Turin, Italy, October 28–31, 2019, Proceedings. editor / Matteo Baldoni ; Mehdi Dastani ; Beishui Liao ; Yuko Sakurai ; Rym Zalila Wenkstern. Springer, 2019. pp. 487-495 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Plasticity is a crucial adaptive characteristic of the brain. Relatively recently mechanisms have been found showing that plasticity itself is controlled by what is called metaplasticity. In this paper a modeling environment is introduced to develop and simulate reified temporal-causal network models that can be applied for cognitive agent models. It is shown how this environment is a useful tool to model plasticity combined with metaplasticity.",

author = "Jan Treur",

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doi = "10.1007/978-3-030-33792-6_33",

language = "English",

isbn = "9783030337919",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Treur, J 2019, A Modeling Environment for Reified Temporal-Causal Networks: Modeling Plasticity and Metaplasticity in Cognitive Agent Models. in M Baldoni, M Dastani, B Liao, Y Sakurai & R Zalila Wenkstern (eds), PRIMA 2019: Principles and Practice of Multi-Agent Systems: 22nd International Conference, Turin, Italy, October 28–31, 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11873 LNAI, Springer, pp. 487-495, 22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019, Turin, Italy, 28/10/19. https://doi.org/10.1007/978-3-030-33792-6_33

A Modeling Environment for Reified Temporal-Causal Networks: Modeling Plasticity and Metaplasticity in Cognitive Agent Models. / Treur, Jan.
PRIMA 2019: Principles and Practice of Multi-Agent Systems: 22nd International Conference, Turin, Italy, October 28–31, 2019, Proceedings. ed. / Matteo Baldoni; Mehdi Dastani; Beishui Liao; Yuko Sakurai; Rym Zalila Wenkstern. Springer, 2019. p. 487-495 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11873 LNAI).

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

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Treur J. A Modeling Environment for Reified Temporal-Causal Networks: Modeling Plasticity and Metaplasticity in Cognitive Agent Models. In Baldoni M, Dastani M, Liao B, Sakurai Y, Zalila Wenkstern R, editors, PRIMA 2019: Principles and Practice of Multi-Agent Systems: 22nd International Conference, Turin, Italy, October 28–31, 2019, Proceedings. Springer. 2019. p. 487-495. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2019 Oct 21. doi: 10.1007/978-3-030-33792-6_33

A Modeling Environment for Reified Temporal-Causal Networks: Modeling Plasticity and Metaplasticity in Cognitive Agent Models

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