How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network

Cruse H, Schilling M (2013)
Frontiers in Psychology 4: 324.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
OA
Abstract / Bemerkung
An artificial neural network called reaCog is described which is based on a decentralized, reactive and embodied architecture developed to control non-trivial hexapod walking in an unpredictable environment (Walknet) while using insect-like navigation (Navinet). In reaCog, these basic networks are extended in such a way that the complete system, reaCog, adopts the capability of inventing new behaviors and – via internal simulation – of planning ahead. This cognitive expansion enables the reactive system to be enriched with additional procedures. Here, we focus on the question to what extent properties of phenomena to be characterized on a different level of description as for example consciousness can be found in this minimally cognitive system. Adopting a monist view, we argue that the phenomenal aspect of mental phenomena can be neglected when discussing the function of such a system. Under this condition, reaCog is discussed to be equipped with properties as are bottom-up and top-down attention, intentions, volition, and some aspects of Access Consciousness. These properties have not been explicitly implemented but emerge from the cooperation between the elements of the network. The aspects of Access Consciousness found in reaCog concern the above mentioned ability to plan ahead and to invent and guide (new) actions. Furthermore, global accessibility of memory elements, another aspect characterizing Access Consciousness is realized by this network. reaCog allows for both reactive/automatic control and (access-) conscious control of behavior. We discuss examples for interactions between both the reactive domain and the conscious domain. Metacognition or Reflexive Consciousness is not a property of reaCog. Possible expansions are discussed to allow for further properties of Access Consciousness, verbal report on internal states, and for Metacognition. In summary, we argue that already simple networks allow for properties of consciousness if leaving the phenomenal aspect aside.
Erscheinungsjahr
2013
Zeitschriftentitel
Frontiers in Psychology
Band
4
Seite(n)
324
ISSN
1664-1078
eISSN
1664-1078
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Deutsche Forschungsgemeinschaft und die Universität Bielefeld gefördert.
Page URI
https://pub.uni-bielefeld.de/record/2610958

Zitieren

Cruse H, Schilling M. How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network. Frontiers in Psychology. 2013;4:324.
Cruse, H., & Schilling, M. (2013). How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network. Frontiers in Psychology, 4, 324. doi:10.3389/fpsyg.2013.00324
Cruse, Holk, and Schilling, Malte. 2013. “How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network”. Frontiers in Psychology 4: 324.
Cruse, H., and Schilling, M. (2013). How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network. Frontiers in Psychology 4, 324.
Cruse, H., & Schilling, M., 2013. How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network. Frontiers in Psychology, 4, p 324.
H. Cruse and M. Schilling, “How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network”, Frontiers in Psychology, vol. 4, 2013, pp. 324.
Cruse, H., Schilling, M.: How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network. Frontiers in Psychology. 4, 324 (2013).
Cruse, Holk, and Schilling, Malte. “How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network”. Frontiers in Psychology 4 (2013): 324.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Copyright Statement:
Dieses Objekt ist durch das Urheberrecht und/oder verwandte Schutzrechte geschützt. [...]
Volltext(e)
Access Level
OA Open Access
Zuletzt Hochgeladen
2019-09-06T09:18:16Z
MD5 Prüfsumme
64affdda617a8153d8d510a70f7ac240


3 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

ReaCog, a Minimal Cognitive Controller Based on Recruitment of Reactive Systems.
Schilling M, Cruse H., Front Neurorobot 11(), 2017
PMID: 28194106
Mental representation and motor imagery training.
Schack T, Essig K, Frank C, Koester D., Front Hum Neurosci 8(), 2014
PMID: 24904368
A hexapod walker using a heterarchical architecture for action selection.
Schilling M, Paskarbeit J, Hoinville T, Hüffmeier A, Schneider A, Schmitz J, Cruse H., Front Comput Neurosci 7(), 2013
PMID: 24062682

65 References

Daten bereitgestellt von Europe PubMed Central.

Neural reuse: a fundamental organizational principle of the brain.
Anderson ML., Behav Brain Sci 33(4), 2010
PMID: 20964882

Baars B.., 1988
Crossing large gaps: a simulation study of stick insect behaviour
Bläsing B.., 2006
Expérience sur la vision
Bloch A.., 1885
On a confusion about a function of consciousness
Block N.., 1995

Bratman M.., 1987
A neural theory of visual attention and short-term memory (NTVA).
Bundesen C, Habekost T, Kyllingsbæk S., Neuropsychologia 49(6), 2010
PMID: 21146554
Simulation and self-knowledge: a defence of the theory-theory
Carruthers P.., 1996

Chalmers D.., 1996
Computational correlates of consciousness
Cleeremans A.., 2005
Consciousness and metarepresentation: a computational sketch.
Cleeremans A, Timmermans B, Pasquali A., Neural Netw 20(9), 2007
PMID: 17904799
Consciousness cannot be separated from function.
Cohen MA, Dennett DC., Trends Cogn. Sci. (Regul. Ed.) 15(8), 2011
PMID: 21807333
The talking stick: a cognitive system in a nutshell
Cruse H.., 2010
Getting cognitive
Cruse H., Schilling M.., 2010
From egocentric systems to systems allowing for Theory of Mind and mutualism
Cruse H., Schilling M.., 2011
No need for a cognitive map: decentralized memory for insect navigation.
Cruse H, Wehner R., PLoS Comput. Biol. 7(3), 2011
PMID: 21445233
Experimental and theoretical approaches to conscious processing.
Dehaene S, Changeux JP., Neuron 70(2), 2011
PMID: 21521609

Dennett D.., 1991
Neural mechanisms of selective visual attention.
Desimone R, Duncan J., Annu. Rev. Neurosci. 18(), 1995
PMID: 7605061
Behaviour-based modelling of hexapod locomotion: linking biology and technical application.
Durr V, Schmitz J, Cruse H., Arthropod structure & development. 33(3), 2004
PMID: IND43653723
Imitation, mind reading, and simulation
Goldman A.., 2005
Volition in action: intentions, control dilemmas, and the dynamic regulation of cognitive control
Goschke T.., 2013
Consciousness & the small network argument.
Herzog MH, Esfeld M, Gerstner W., Neural Netw 20(9), 2007
PMID: 17900860
Learning and retrieval of memory elements in a navigation task
Hoinville T., Wehner R., Cruse H.., 2012
Robots with internal models: a route to machine consciousness?
Holland O., Goodman R.., 2003
Attention and consciousness: two distinct brain processes.
Koch C, Tsuchiya N., Trends Cogn. Sci. (Regul. Ed.) 11(1), 2006
PMID: 17129748
How rich is consciousness? The partial awareness hypothesis.
Kouider S, de Gardelle V, Sackur J, Dupoux E., Trends Cogn. Sci. (Regul. Ed.) 14(7), 2010
PMID: 20605514
Inquiry into intentional systems I: issues in ecological physics
Kugler P., Shaw R., Vicente K., Kinsella-Shaw J.., 1990

Lakoff G., Núñez R.., 2000
Empirical support for higher-order theories of conscious awareness.
Lau H, Rosenthal D., Trends Cogn. Sci. (Regul. Ed.) 15(8), 2011
PMID: 21737339
PRODUCTION OF THRESHOLD LEVELS OF CONSCIOUS SENSATION BY ELECTRICAL STIMULATION OF HUMAN SOMATOSENSORY CORTEX.
LIBET B, ALBERTS WW, WRIGHT EW Jr, DELATTRE LD, LEVIN G, FEINSTEIN B., J. Neurophysiol. 27(), 1964
PMID: 14194958
Learning from the spinal cord.
Loeb GE., J. Physiol. (Lond.) 533(Pt 1), 2001
PMID: 11351019

McFarland D., Bösser T.., 1993
Cognition in invertebrates
Menzel R., Brembs B., Giurfa M.., 2007
Different conceptions of embodiment
Metzinger T.., 2006

Metzinger T.., 2009
Kinematic networks. A distributed model for representing and regularizing motor redundancy.
Mussa Ivaldi FA, Morasso P, Zaccaria R., Biol Cybern 60(1), 1988
PMID: 3214648
Talking the talk is like walking the walk: a computational model of verbal aspect
Narayanan S.., 1997

Neisser U.., 1967
Attention to action. willed and automatic control of behavior
Norman D., Shallice T.., 1986
Toward a Dynamic Theory of Intentions
Pacherie E.., 2006
Does the chimpanzee have a theory of mind?
Premack D., Woodruff G.., 1978
How many kinds of consciousness?
Rosenthal DM., Conscious Cogn 11(4), 2002
PMID: 12470629

Rumelhart D., McClelland J.., 1986
Radial basis function neural networks versus fuzzy models to predict return of consciousness after general anesthesia.
Nunes CS, Mendonca TF, Amorim P, Ferreira DA, Antunes LM., Conf Proc IEEE Eng Med Biol Soc 2(), 2004
PMID: 17271814
Identifying phenomenal consciousness.
Schier E., Conscious Cogn 18(1), 2008
PMID: 18501635
Universally manipulable body models – dual quaternion representations in layered and dynamic MMCs
Schilling M.., 2011
Hierarchical MMC networks as a manipulable body model
Schilling M., Cruse H.., 2007
The evolution of cognition – from first order to second order embodiment
Schilling M., Cruse H.., 2008
Grounding an internal body model of a hexapod walker – control of curve walking in a biological inspired robot–control of curve walking in a biological inspired robot
Schilling M., Paskarbeit J., Schmitz J., Schneider A., Cruse H.., 2012
Biomechatronics for of embodied intelligence an insectoid robot
Schneider A., Paskarbeit J., Schäffersmann M., Schmitz J.., 2011
Local control mechanisms in six-legged walking
Schilling M., Schneider A., Cruse H., Schmitz J.., 2008
The symbol grounding problem is solved, so what's next?
Steels L.., 2007
Über das Marionettentheater
von H.., 1810

Vision G.., 2011
The human Turing machine: a neural framework for mental programs.
Zylberberg A, Dehaene S, Roelfsema PR, Sigman M., Trends Cogn. Sci. (Regul. Ed.) 15(7), 2011
PMID: 21696998
Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Quellen

PMID: 23785343
PubMed | Europe PMC

Suchen in

Google Scholar