Abstract
This paper shows how spatial cognition and the ability to orient in a closed arena can also emerge in artificial organisms with no sensory apparatus. The control systems (Artificial Neural Networks) of some populations of simulated robots have been evolved in an experimental set-up that is usually used to study spatial cognition of real organisms. Some robots were endowed with a normal perceptive apparatus (infrared sensors and on-board camera), some others had no means of getting information from environment. The control systems of this latter class of robots received stimulation from self-generated input: the feedback of their motor action or the activation of an internal clock. Both kinds of robot learnt some strategies similar to the ones observed in natural organisms. The robots without sensory apparatus displayed a greater amount of micro-behaviour (number of activation patterns of motor output) compared with robots with a normal perceptual system. The amplification of behavioural repertory allowed them to understand the environmental structure even if they couldn’t perceive it.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Elman, J.L.: Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning 7, 195–224 (1991)
Gallistel, C.R.: The organization of Learning. MIT Press, Cambridge (1990)
Gouteux, S., Thinus-Blanc, C., Vauclair, J.: Rhesus Monkeys use geometric and non-geometric information during a reorientation task. Journal of Experimental Psychology: General 130, 505–519 (2001)
Langton, C.G.: Artificial Life: An Overview. The MIT Press/A Bradford Book, Cambridge (1995)
Margules, J., Gallistel, C.R.: Heading in the rat: Determination by environmental shape. Animal Learning and Behavior 16, 404–410 (1988)
Maturana, H.R., Varela, F.J.: The tree of knowledge - The biological roots of human understanding, Shambhala, Boston (1992)
Miglino, O., Lund, H.H.: Do rats need euclidean cognitive maps of the environmental shape? Cognitive Processing 4, 1–9 (2001)
Mitchell, M.: An Introduction to Genetic Algorithms. MIT Press, Cambridge (1996)
Nolfi, S., Floreano, D.: Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines. MIT Press/Bradford, Cambridge (2000)
O’Regan, J.K., Noë, A.: A sensorimotor account of vision and visual consciousness. Behavioral and Brain Sciences 24(5), 939–1011 (2001)
Parisi, D.: Internal Robotics. Connection Science (in Press)
Sovrano, V.A., Bisazza, A., Vallortigara, G.: Modularity and spatial reorientation in a simple mind: Encoding of geometric and non-geometric properties of spatial environment by fish. Cognition 85, 51–59 (2002)
Vallortigara, G., Zanforlin, M., Pasti, G.: Geometric modules in animals’ spatial representation: A test with chicks (Gallus gallus domesticus). Journal of Comparative Psychology 104, 248–254 (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ponticorvo, M., Miglino, O. (2005). Action-Based Cognition: How Robots with No Sensory System Orient Themselves in an Open Field Box. In: Mira, J., Álvarez, J.R. (eds) Mechanisms, Symbols, and Models Underlying Cognition. IWINAC 2005. Lecture Notes in Computer Science, vol 3561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499220_41
Download citation
DOI: https://doi.org/10.1007/11499220_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26298-5
Online ISBN: 978-3-540-31672-5
eBook Packages: Computer ScienceComputer Science (R0)