Summary
We set out to address, in the form of a survey, the fundamental constraints upon self-updating representation in cognitive agents of natural and artificial origin. The foundational epistemic problem encountered by such agents is that of distinguishing errors of representation from inappropriateness of the representational framework. Resolving this conceptual difficulty involves ensuring the empirical falsifiability of both the representational hypotheses and the entities so represented, while at the same time retaining their epistemic distinguishability.
We shall thus argue that perception-action frameworks provide an appropriate basis for the development of an empirically meaningful criterion for validating perceptual categories. In this scenario, hypotheses about the agent’s world are defined in terms of environmental affordances (characterised in terms of the agent’s active capabilities). Agents with the capability to hierarchically-abstract this framework to a level consonant with performing syntactic manipulations and making deductive conjectures are consequently able to form an implicitly symbolic representation of the environment within which new, higher-level, modes of environment manipulation are implied (e.g. tool-use). This abstraction process is inherently open-ended, admitting a wide-range of possible representational hypotheses — only the form of the lowest-level of the hierarchy need be constrained a priori (being the minimally sufficient condition necessary for retention of the ability to falsify high-level hypotheses).
In biological agents capable of autonomous cognitive-updating, we argue that the grounding of such a priori ‘bootstrap’ representational hypotheses is ensured via the process of natural selection.
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.
Similar content being viewed by others
References
Hume D (1999) An Enquiry concerning Human Understanding. Oxford University Press, Oxford/New York
Kant I (1999) Critique of Pure Reason. Cambridge University Press
Heidegger M (1996) Being and Time. Blackwell
Dreyfus H (1972) What Computers Can't Do. New York: Harper and Row
Suber P. Mind and baud rate. E-print of the Phil. Dept., Earlham College, Retr. 13/6/2005 http://www.earlham.edu/_peters/writing/baudrate.htm
Winograd T (1980) What does it mean to understand language?, Cognitive Science 4(3):209–242. Reprinted in D. Norman (ed.), Perspectives on Cognitive Science, Ablex and Erlbaum Associates, 1981, 231-264
Gödel K (1931) Über formal unentscheidbare stäze der principia math. & verwandter systeme, I Monatshefte für Mathematik und Physik (38):173–198
Breuer T (2000) In: M Carrier GM L Ruetsche (ed.) Science at Century's End: Philosophical Questions on the Progress and Limits of Science. Pittsburgh & Konstanz, University of Pittsburgh Press & Universitätsverlag Konstanz
Breuer T (1995) The impossibility of exact state self-measurements, Philosophy of Science 62:197–214
Winograd T, Flores F (1986) Understanding Computers and Cognition. Addison-Wesley, Reading, MA
McCarthy J, Hayes P (1969) Some philosophical problems from the standpoint of artificial intelligence, Machine Intelligence (4):463–502
Quine WVO (1960) Word and Object. NY: John Wiley and Sons, MIT
Wittgenstein L (2001) Philosophical investigations : the German text with a revised English translation by Ludwig Wittgenstein. Oxford : Blackwell
Millikan RG (1987) Language, Thought, and Other Biological Categories: New Foundations for Realism. The MIT Press; Reprint edition
Sipper M (1995) An introduction to artificial life., Explorations in Artificial Life (special issue of AI Expert) 4–8
Marr D (1982) Vision: A Computational Approach. Freeman & Co., San Fr.
Gärdenfors P (1994) How logic emerges from the dynamics of information, Logic and Information Flow 49–77
Granlund G (2003) Organization of Architectures for Cognitive Vision Systems, In: Proceedings of Workshop on Cognitive Vision. Schloss Dagstuhl, Germany
Magee D, Needham CJ, Santos P, Cohn AG, Hogg DC (2004) Autonomous learning for a cognitive agent using continuous models and inductive logic programming from audio-visual input, In: Proc. of the AAAI Workshop on Anchoring Symbols to Sensor Data
Brooks RA (1991) Intelligence without representation, Artificial Intelligence 47:139–159
Newell A, Simon H (1976) The Theory of Human Problem Solving; reprinted in Collins & Smith (eds.), In: Readings in Cognitive Science, section 1.3.
Pinker S, Bloom P (1990) Natural language and natural selection, Behavioural and Brain Sciences 13(4):707–784
Marshall J, Blank D, Meeden L (2004) An emergent framework for selfmotivation in developmental robotics, In: Proc. of the Third International Conference on Development and Learning (ICDL '04). Salk Inst.
Franklin S, Garzon M (1991) Neural Computability, In: Omidvar O (ed.) Progress in Neural Networks, vol. 1. Ablex
Wolff JG (1987) Cognitive development as optimisation, In: Bolc L (ed.) Computational Models of Learning, 161–205. Springer-Verlag, Heidelberg
Dewey J (1896) The reex arc concept in psychology, The Psychological Review (3):356–370
Gibson JJ (1979) The ecological approach to visual perception. Houghton-Mifflin, Boston
McGrenere J, Ho W (2000) Affordances: Clarifying and Evolving a Concept, In: Proceedings of Graphics Interface 2000, 179{186. Montreal, Canada
Lakoff G, Johnson M (1999) Philosophy in the Flesh : The Embodied Mind and Its Challenge to Western Thought. Harper Collins Publishers
Glenberg A (1997) What memory is for, Behavioral and Brain Sciences 20(1):1–55
Berlucchi F, Aglioti S (1997) The body in the brain: neural bases of corporeal awareness, Trends in Neuroscience 20(5):60–564
Piaget J (1970) Genetic Epistemology. Columbia University Press, New York
Rohrer T (2001) Pragmatism, Ideology and Embodiment: William James and the Philosophical Foundations of Cognitive Linguistics, In: Sandriklogou, Dirven (eds.) Language and Ideology: Cognitive Theoretical Approaches, 49-82. Amsterdam: John Benjamins
Perry J (1997) Myself and I, In: Stamm M (ed.) Philosophie in Sythetisher Absicht, 83–103. Stuttgart:Klett-Cotta
Bermudez JL (2001) Non-conceptual self-consciousness and cognitive science, Synthese (129):129–149
Metzinger T (2003) Phenomenal transparency and cognitive self-reference, Phenomenology and the Cognitive Sciences (2):353–393
Viezzer M (2001) Dynamic Ontologies or How to Build Agents That Can Change Their Mind. Ph.D. Thesis, University of Birmingham, UK
Pinker S (1995) The Language Instinct: The New Science of Language and Mind. Penguin Books Ltd. ISBN: 0140175296
Harnad S (1990) The symbol grounding problem, Physica D (42):335–346
Steels L (1997) The origins of syntax in visually grounded robotic agents, In: Pollack M (ed.) Proceedings of the 10th IJCAI, Nagoya, 1632{1641. AAAI Press, Menlo-Park Ca.
Harrison JE, Baron-Cohen S (1996) Synaesthesia: Classic and Contemporary Readings. Blackwell Publishers
Saunders J, Knill DC (2004) Visual feedback control of hand movements, J of Neuroscience 24(13):3223–3234
Schlicht EJ, Schrater PR (2003) Bayesian model for reaching and grasping peripheral and occluded targets, Journal of Vision 3(9):261
Brooks RA (1986) A robust layered control system for a mobile robot, IEEE Journal of Robotics and Automation 14(23)
Modayil J. Bootstrap learning a perceptually grounded object ontology. Retr. 9/5/2005 http://www.cs.utexas.edu/users/modayil/modayil-proposal.pdf
Nehaniv CL, Polani D, Dautenhahn K, te Boekhorst R, Canamero L (2002) In: Standish B Abbass (ed.) Artificial Life VIII, 345–349. MIT Press
Sun R (2004) Desiderata for cog. architectures, Philosophical Psychology 17(3)
Stein LA (1991) Imagination and situated cognition. Tech. Rep. A.I. Memo No. 27, MIT AI Laboratory
Windridge D, Kittler J (2007) Open-Ended Inference of Relational Representations in the COSPAL Perception-Action Architecture, In: Proc. of International Conf. on Machine Vision Applications (ICVS 2007). Germany
Quine WVO (1977) Ontological Relativity. Columbia
Popper K (1959) The Logic of Scientific Discovery. (translation of Logik der Forschung). Hutchinson, London
Dawkins R (1989) The Sel_sh Gene (2nd ed.). OUP
Hobson J (1988) The Dreaming Brain. Basic Books, New York
Gallese V, Goldman A (1998) Mirror neurons and the simulation theory of mind-reading, Trends in Cognitive Sciences 2(2)
Windridge D (2005) Cognitive bootstrapping: A survey of bootstrap mechanisms for emergent cognition. Tech. Rep. VSSP-TR-2/2005, CVSSP, The University of Surrey, Guildford, Surrey, GU2 7XH, UK
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Windridge, D., Kittler, J. (2008). Epistemic Constraints on Autonomous Symbolic Representation in Natural and Artificial Agents. In: Smolinski, T.G., Milanova, M.G., Hassanien, AE. (eds) Applications of Computational Intelligence in Biology. Studies in Computational Intelligence, vol 122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78534-7_16
Download citation
DOI: https://doi.org/10.1007/978-3-540-78534-7_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78533-0
Online ISBN: 978-3-540-78534-7
eBook Packages: EngineeringEngineering (R0)