---
abstract: 'This article explores an application of Bayesian programming to behaviours for synthetic video games characters. We address the problem of real-time reactive selection of elementary behaviours for an agent playing a first person shooter game. We show how Bayesian programming can lead to condensed and easier formalisation of finite state machine-like behaviour selection, and lend itself to learning by imitation, in a fully transparent way for the player.'
altloc:
  - http://www-laplace.imag.fr/publications/Rayons/lehy04.pdf
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creators_name:
  - family: Le Hy
    given: R
    honourific: ''
    lineage: ''
  - family: Arrigoni
    given: A
    honourific: ''
    lineage: ''
  - family: Bessiere
    given: P
    honourific: Dr
    lineage: ''
  - family: Lebeltel
    given: O
    honourific: Dr
    lineage: ''
date: 2004
date_type: published
datestamp: 2004-08-10
department: ~
dir: disk0/00/00/37/44
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editors_id: []
editors_name:
  - family: Billard
    given: A
    honourific: ''
    lineage: ''
  - family: Siegwart
    given: R
    honourific: Prof.
    lineage: ''
eprint_status: archive
eprintid: 3744
fileinfo: /style/images/fileicons/application_pdf.png;/3744/1/lehy04.pdf
full_text_status: public
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keywords: Bayesian programming; Video games characters; Finite state machine; Learning by imitation
lastmod: 2011-03-11 08:55:39
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metadata_visibility: show
note: ~
number: ~
pagerange: 177-185
pubdom: TRUE
publication: 'Robotics and Autonomous Systems (Elsevier) Special issue: Robot Learning from Demonstration'
publisher: Elsevier
refereed: FALSE
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relation_type: []
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reportno: ~
rev_number: 12
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status_changed: 2007-09-12 16:53:10
subjects:
  - comp-sci-robot
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title: Teaching Bayesian Behaviours to Video Game Characters
type: journalp
userid: 4357
volume: 47
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