---
abstract: 'We suppose the functional parts combination (FPC) model, whereby a problem solving strategy is acquired depending on the tasks given. The model is based on the neuroscientific fact that each cerebral cortical area has a different role and is selectively activated depending on the task. FPC model is a meta learning model that consists of a set of functional parts and a sequence of control signals that specifies their combination. The functional parts are combined depending on the situation, to realize a processing circuit required for the situation. We use genetic algorithm for searching the control signals. We examine the model by evaluating the difference in acquired behavior of (1) two agents with different functional parts working on the same navigational task and (2) two agents with the same functional parts working on different tasks. We show that the agent using FPC model acquires learning strategies suitable for the given problems.'
altloc:
  - http://www.lucs.lu.se/ftp/pub/LUCS_Studies/LUCS94/Ogawa.pdf
chapter: ~
commentary: ~
commref: ~
confdates: 'August 10-11, 2002'
conference: 'Second International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems'
confloc: 'Edinburgh, Scotland'
contact_email: ~
creators_id: []
creators_name:
  - family: Ogawa
    given: Akitoshi
    honourific: ''
    lineage: ''
  - family: Omori
    given: Takashi
    honourific: ''
    lineage: ''
date: 2002
date_type: published
datestamp: 2003-10-04
department: ~
dir: disk0/00/00/25/24
edit_lock_since: ~
edit_lock_until: ~
edit_lock_user: ~
editors_id: []
editors_name:
  - family: Prince
    given: Christopher G.
    honourific: ''
    lineage: ''
  - family: Demiris
    given: Yiannis
    honourific: ''
    lineage: ''
  - family: Marom
    given: Yuval
    honourific: ''
    lineage: ''
  - family: Kozima
    given: Hideki
    honourific: ''
    lineage: ''
  - family: Balkenius
    given: Christian
    honourific: ''
    lineage: ''
eprint_status: archive
eprintid: 2524
fileinfo: /style/images/fileicons/application_pdf.png;/2524/1/Ogawa.pdf
full_text_status: public
importid: ~
institution: ~
isbn: ~
ispublished: pub
issn: ~
item_issues_comment: []
item_issues_count: 0
item_issues_description: []
item_issues_id: []
item_issues_reported_by: []
item_issues_resolved_by: []
item_issues_status: []
item_issues_timestamp: []
item_issues_type: []
keywords: 'functional parts combination, FPC, meta learning, genetic algorithm, agent simulation'
lastmod: 2011-03-11 08:55:04
latitude: ~
longitude: ~
metadata_visibility: show
note: ~
number: ~
pagerange: 125-132
pubdom: TRUE
publication: ~
publisher: Lund University Cognitive Studies
refereed: TRUE
referencetext: ~
relation_type: []
relation_uri: []
reportno: ~
rev_number: 12
series: ~
source: ~
status_changed: 2007-09-12 16:45:31
subjects:
  - comp-sci-mach-learn
  - comp-sci-art-intel
  - comp-sci-robot
succeeds: ~
suggestions: ~
sword_depositor: ~
sword_slug: ~
thesistype: ~
title: 'Looking for a suitable strategy for each problem - Multiple tasks approach to navigation learning task'
type: confpaper
userid: 3507
volume: 94
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