A second-order adaptive social-cognitive agent model for prisoner recidivism

Dorien Melman, Janne B. Ploeger, Jan Treur*

*Corresponding author for this work

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

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Abstract

In this study, a second-order adaptive social-cognitive agent model is introduced to examine prisoner recidivism. For comparison between different kinds of prisons and prison policies, recidivism rates from Norway and the USA are used. Two scenarios were used to model the effects of environmental, prison-related, and personal influences on recidivism rates. The presented adaptive social-cognitive agent model is based on a second-order reified network model. The model allows to computationally explore the effects on prisoner recidivism and the learning process for a prisoner’s social-cognitive state of mind as a main determinant of recidivism risk.

Original languageEnglish
Title of host publicationHighlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection
Subtitle of host publicationInternational Workshops of PAAMS 2020, L'Aquila, Italy, October 7–9, 2020, Proceedings
EditorsFernando De La Prieta, Philippe Mathieu, Jaime Andrés Rincón Arango, Elena Del Val, Vicente Julian, Alia El Bolock, Jaume Jordán Prunera, João Carneiro, Rubén Fuentes, Fernando Lopes
PublisherSpringer
Pages154-167
Number of pages14
ISBN (Electronic)9783030519995
ISBN (Print)9783030519988
DOIs
Publication statusPublished - 2020
Event18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020 - L’Aquila, Italy
Duration: 7 Oct 20209 Oct 2020

Publication series

NameCommunications in Computer and Information Science
Volume1233 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020
Country/TerritoryItaly
CityL’Aquila
Period7/10/209/10/20

Keywords

  • Adaptive agent model
  • Hebbian learning
  • Prisoner recidivism

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