eprintid: 1428
rev_number: 7
eprint_status: archive
userid: 1
dir: disk0/00/00/14/28
datestamp: 2001-02-07 13:55:00
lastmod: 2014-01-13 14:15:00
status_changed: 2012-08-14 15:00:46
type: masterThesis
metadata_visibility: show
creators_name: Schenck, Wolfram
title: A connectionist approach to human planning
ispublished: pub
subjects: ddc-300
divisions: i-100200
keywords: Kognitive Modellierung , Kognitive Psychologie , Kognitionswissenschaft , Hierarchisches Elman-Netzwerk , Plan-A-DayConnectionism , Neural Network , Planning , Plan-A-Day , Cognitive Science
cterms_swd: Konnektionismus
cterms_swd: Neuronales Netz
cterms_swd: Planung
cterms_swd: Kognition
cterms_swd: Computersimulation
abstract: In the present thesis, a connectionist model (called EVA) was developed for the simulation of human planning behavior in the domain of Plan-A-Day.  Plan-A-Day is a diagnostic instrument for the assessment of planning capabilities (Funke & Krüger, 1995), which provides a computer scenario in which the subjects must find an optimal sequence for several scheduled appointments by applying operators from a predefined set.  EVA is designed to produce sequences of these operators which are applied within Plan-A-Day.  In this way, EVA is intended to show the same kind of operationally defined planning behavior as human subjects do.  EVA comprises three sub-networks of the backpropagation-class, two of which are hierarchical Elman networks.  Based on the situated action account (Clark, 1997; Suchman, 1987), the input of EVA is for the most part a representation of the current state of the Plan-A-Day scenario.  The data obtained by simulation runs is compared to empirical data obtained by a study with 45 human subjects.  The comparison is carried out with regard to indicators reflecting planning performance, as well as characteristics of the process of planning.  The fit between simulated and human data is good enough to allow certain theoretical claims.  EVA provides evidence that simple pattern transformation devices like connectionist networks are capable of performing human-like planning, if these networks are thoroughly embedded into their environment, as it is demanded by the situated action account.  EVA demonstrates that even conventional connectionist models are applicable to tasks from the field of high-level cognition like planning or problem-solving, which were mostly reserved for symbol-processing models until now.
class_scheme: thes_soz
date: 2001
date_type: published
id_scheme: DOI
id_number: 10.11588/heidok.00001428
ppn_swb: 1643185012
own_urn: urn:nbn:de:bsz:16-heidok-14287
language: eng
bibsort: SCHENCKWOLACONNECTIO2001
full_text_status: public
citation:   Schenck, Wolfram  (2001) A connectionist approach to human planning.  [Master's thesis]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/1428/1/conplan.pdf