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abstract: A technique for modelling economic agents with bounded and procedural rationality is presented. In this technique an agent has a population of mental models which evolve. This evolution is its learning process. This is embedded within an agent architecture which then exhibits several qualitative characteristics relevant to modelling human-like agents. Two example models using this technique are presented. The first is of agents attempting to learn their own utility function in the presence of structural change. The second is an extension of Brian Arthur's `El Farol Bar' model where evolutionary learning and communication is added.
altloc:
  - http://www.cpm.mmu.ac.uk/cpmrep33.html
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commentary: ~
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creators_id: []
creators_name:
  - family: Edmonds
    given: Bruce
    honourific: ''
    lineage: ''
date: 1998
date_type: published
datestamp: 1998-08-07
department: ~
dir: disk0/00/00/05/11
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editors_id: []
editors_name:
  - family: Brenner
    given: Thomas
    honourific: ''
    lineage: ''
eprint_status: archive
eprintid: 511
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full_text_status: public
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ispublished: inpress
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keywords: 'modelling, simulation, bounded rationality, multi agent system, mental models, evolution'
lastmod: 2011-03-11 08:54:01
latitude: ~
longitude: ~
metadata_visibility: show
note: ~
number: ~
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pubdom: FALSE
publication: Computational Techniques for Modelling Learning in Economics
publisher: Kluwer Academic
refereed: FALSE
referencetext: ~
relation_type: []
relation_uri: []
reportno: ~
rev_number: 14
series: ~
source: ~
status_changed: 2007-09-12 16:29:35
subjects:
  - cog-psy
  - comp-sci-art-intel
  - comp-sci-complex-theory
  - comp-sci-mach-learn
  - evol-psy
  - soc-psy
succeeds: ~
suggestions: ~
sword_depositor: ~
sword_slug: ~
thesistype: ~
title: Modelling Bounded Rationality In Agent-Based Simulations using the Evolution of Mental Models
type: bookchapter
userid: 192
volume: ~
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