Evolving agent cognition with Netlogo LevelSpace

Bryan Head, Arthur Hjorth, Corey Brady, Uri Wilensky

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish (US)
Title of host publication2015 Winter Simulation Conference, WSC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3122-3123
Number of pages2
ISBN (Electronic)9781467397438
DOIs
StatePublished - Feb 16 2016
EventWinter Simulation Conference, WSC 2015 - Huntington Beach, United States
Duration: Dec 6 2015Dec 9 2015

Publication series

NameProceedings - Winter Simulation Conference
Volume2016-February
ISSN (Print)0891-7736

Other

OtherWinter Simulation Conference, WSC 2015
CountryUnited States
CityHuntington Beach
Period12/6/1512/9/15

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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