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

Jan Treur*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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 languageEnglish
Title of host publicationPRIMA 2019: Principles and Practice of Multi-Agent Systems
Subtitle of host publication22nd International Conference, Turin, Italy, October 28–31, 2019, Proceedings
EditorsMatteo Baldoni, Mehdi Dastani, Beishui Liao, Yuko Sakurai, Rym Zalila Wenkstern
PublisherSpringer
Pages487-495
Number of pages9
ISBN (Electronic)9783030337926
ISBN (Print)9783030337919
DOIs
Publication statusPublished - 2019
Event22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019 - Turin, Italy
Duration: 28 Oct 201931 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11873 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019
CountryItaly
CityTurin
Period28/10/1931/10/19

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