Evolving agent cognition with Netlogo LevelSpace

Bryan Head; Arthur Hjorth; Corey Brady; Uri Wilensky

doi:10.1109/WSC.2015.7408430

Evolving agent cognition with Netlogo LevelSpace

Bryan Head, Arthur Hjorth, Corey Brady, Uri Wilensky

School of Education and Social Policy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

Any agent-based model (ABM) involving agents that think or make decisions must inevitably have some model of agent cognition. Often, this cognitive model is incredibly simple, such as choosing actions at random or based on simple conditionals. In reality, agent cognition can be complex and dynamic, and for some models, this process can be worthy of its own dedicated ABM. The LevelSpace extension (Hjorth, Head and Wilensky, 2015) for NetLogo (Wilensky 1999) allows NetLogo models to open instances of other NetLogo models and interact with them. We demonstrate a method for using LevelSpace to simulate agents with complex, evolving cognitive models. We give the agents in a NetLogo predator-prey model "brains," themselves represented as independent instances of a NetLogo neural network model.

Original language	English (US)
Title of host publication	2015 Winter Simulation Conference, WSC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3122-3123
Number of pages	2
ISBN (Electronic)	9781467397438
DOIs	https://doi.org/10.1109/WSC.2015.7408430
State	Published - Feb 16 2016
Event	Winter Simulation Conference, WSC 2015 - Huntington Beach, United States Duration: Dec 6 2015 → Dec 9 2015

Publication series

Name	Proceedings - Winter Simulation Conference
Volume	2016-February
ISSN (Print)	0891-7736

Other

Other	Winter Simulation Conference, WSC 2015
Country/Territory	United States
City	Huntington Beach
Period	12/6/15 → 12/9/15

ASJC Scopus subject areas

Software
Modeling and Simulation
Computer Science Applications

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/WSC.2015.7408430

Cite this

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title = "Evolving agent cognition with Netlogo LevelSpace",

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doi = "10.1109/WSC.2015.7408430",

language = "English (US)",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3122--3123",

booktitle = "2015 Winter Simulation Conference, WSC 2015",

address = "United States",

note = "Winter Simulation Conference, WSC 2015 ; Conference date: 06-12-2015 Through 09-12-2015",

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Head, B, Hjorth, A, Brady, C & Wilensky, U 2016, Evolving agent cognition with Netlogo LevelSpace. in 2015 Winter Simulation Conference, WSC 2015., 7408430, Proceedings - Winter Simulation Conference, vol. 2016-February, Institute of Electrical and Electronics Engineers Inc., pp. 3122-3123, Winter Simulation Conference, WSC 2015, Huntington Beach, United States, 12/6/15. https://doi.org/10.1109/WSC.2015.7408430

Evolving agent cognition with Netlogo LevelSpace. / Head, Bryan; Hjorth, Arthur; Brady, Corey et al.
2015 Winter Simulation Conference, WSC 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 3122-3123 7408430 (Proceedings - Winter Simulation Conference; Vol. 2016-February).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Evolving agent cognition with Netlogo LevelSpace

AU - Head, Bryan

AU - Hjorth, Arthur

AU - Brady, Corey

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PY - 2016/2/16

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AB - Any agent-based model (ABM) involving agents that think or make decisions must inevitably have some model of agent cognition. Often, this cognitive model is incredibly simple, such as choosing actions at random or based on simple conditionals. In reality, agent cognition can be complex and dynamic, and for some models, this process can be worthy of its own dedicated ABM. The LevelSpace extension (Hjorth, Head and Wilensky, 2015) for NetLogo (Wilensky 1999) allows NetLogo models to open instances of other NetLogo models and interact with them. We demonstrate a method for using LevelSpace to simulate agents with complex, evolving cognitive models. We give the agents in a NetLogo predator-prey model "brains," themselves represented as independent instances of a NetLogo neural network model.

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M3 - Conference contribution

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Evolving agent cognition with Netlogo LevelSpace

Abstract

Publication series

Other

ASJC Scopus subject areas

UN SDGs

Access to Document

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