Abstract
This paper addresses the questions concerningthe relationship between scientific andcognitive processes. The fact that both,science and cognition, aim at acquiring somekind of knowledge or representationabout the “world” is the key for establishing alink between these two domains. It turns outthat the constructivist frameworkrepresents an adequate epistemologicalfoundation for this undertaking, as its focusof interest is on the (constructive)relationship between the world and itsrepresentation. More specifically, it will beshown how cognitive processes and their primaryconcern to construct a representation of theenvironment and to generate functionallyfitting behavior can act as the basis forembedding the activities and dynamics of theprocess of science in them by making use ofconstructivist concepts, such as functionalfitness, structure determinedness, etc.Cognitive science and artificiallife provide the conceptual framework of representational spaces and their interactionbetween each other and with the environmentenabling us to establish this link betweencognitive processes and thedevelopment/dynamics of scientific theories.The concepts of activation, synaptic weight,and genetic (representational) spaces arepowerful tools which can be used as“explanatory vehicles”for a cognitivefoundation of science, more specifically forthe “context of discovery” (i.e., thedevelopment, construction, and dynamics ofscientific theories and paradigms).Representational spaces do not only offer us abetter understanding of embedding science incognition, but also show, how theconstructivist framework, both, can act as anadequate epistemological foundation for theseprocesses and can be instantiated by theserepresentational concepts from cognitivescience. The final part of this paper addresses somemore fundamental questions concerning thepositivistic and constructivist understandingof science and human cognition. Among otherthings it is asked, whether a purelyfunctionalist and quantitative view of theworld aiming almost exclusively at itsprediction and control is really satisfying forour intellect (having the goal of achieving aprofound understanding of reality).
Similar content being viewed by others
REFERENCES
Arbib, M.A. (ed.): 1995, The Handbook of Brain Theory and Neural Networks. Cambridge, MA: MIT Press.
Ashby, R.W.: 1964, An Introduction to Cybernetics. London: Methuen. Bechtel, W. (1988). Philosophy of Science. An Overview for Cognitive Science. Hillsdale, N.J.: L. Erlbaum.
Belew, R.K.: 1990, Evolution, Learning, and Culture: Computational Metaphors for Adaptive Algorithms. Complex Systems 4: 11–49.
Belew, R.K., J. McInerney and N.N. Schraudolph: 1992, Evolving Networks: Using the Genetic Algorithm with Connectionist Learning. In C.G. Langton, C. Taylor, J.D. Farmer and S. Rasmussen (eds.), Artificial Life II, Redwood City, CA: Addison-Wesley, 511–547.
Berger, P. and M. Singer: 1992, Dealing with Genes: The Language of Heredity. Mill Valley, CA: University Science Books.
Brakel, J.V.: 1994, Cognitive Scientism of Science. Psycoloquy (electronic journal) 5(20) (filename: scientific-cognition.3.vanbrakel).
Brown, T.H., A.H. Ganong, E.W. Kariss and C.L. Keenan: 1990, Hebbian Synapses: Biophysical Mechanisms And Algorithms. Annual Review of Neuroscience 13: 475–511.
Cangelosi, A., D. Parisi and S. Nolfi: 1994, Cell Division and Migration in A Genotype for Neural Networks. Network: computation in Neural Systems 5(4): 497–516.
Churchland, P.M.: 1979, Scientific Realism and the Plasticity of Mind. Cambridge, New York: Cambridge University Press.
Churchland, P.M. (ed.): 1989, A Neurocomputational Perspective – The Nature of Mind and the Structure of Science. Cambridge, MA: MIT Press.
Churchland, P.M.: 1991, A Deeper Unity: Some Feyerabendian Themes in Neurocomputational Form. In G. Munevar (ed.), Beyond Reason: Essays on the Philosophy of Paul Feyerabend. Dordrecht, Boston: Kluwer Academic Publishers, 1–23 (reprinted in R.N. Giere (ed.), Cognitive Models of Science, Minnesota Studies In The Philosophy of Science XV, 1992).
Churchland, P.M.: 1995, The Engine of Reason, The Seat of the Soul. A Philosophical Journey into the Brain. Cambridge, MA: MIT Press.
Churchland, P.M. and P.S. Churchland: 1990, Could a Machine Think? Scientific American 262(1): 32–37.
Churchland, P.S. and T.J. Sejnowski: 1992, The Computational Brain. Cambridge, MA: MIT Press.
Edelman, G.M.: 1988, Topobiology: An Introduction to Molecular Embryology. New York: Basic Books.
Essen, D.C.v., C.H. Anderson and D.J. Felleman: 1992, Information Processing in the Primate Visual System: An Integrated Systems Perspective. Science 255: 419–423.
Fodor, J.A.: 1975, The Language of Thought. New York: Crowell.
Fodor, J.A.: 1981, Representations: Philosophical Essays on the Foundations of Cognitive Science. Cambridge, MA: MIT Press.
Foerster, H.v.: 1973, On Constructing a Reality. In W.F.E. Preiser (ed.), Environmental Design Research, Volume 2. Stroudsburg, PA: Hutchinson & Ross. (reprinted in P. Watzlawick (ed.), The Invented Reality, Norton, 41–61, 1984).
Gazzaniga, M.S. (ed.): 1995, The Cognitive Neurosciences. Cambridge, MA: MIT Press.
Giere, R.N. (ed.): 1992, Cognitive Models of Science, Volume XV of Minnesota Studies in the Philosophy Of Science. Minneapolis: University of Minnesota Press.
Giere, R.N.: 1994, The Cognitive Structure of Scientific Theories. Philosophy of Science 61: 276–296.
Glasersfeld, E.v.: 1984, An Introduction to Radical Constructivism. In P. Watzlawick (ed.), The Invented Reality. New York: Norton, 17–40.
Glasersfeld, E.v.: 1991, Knowing without Metaphysics. Aspects of the Radical Constructivist Position. In F. Steier (ed.), Research and Reflexivity. London; Newbury Park, CA: SAGE Publishers, 12–29.
Glasersfeld, E.v.: 1995, Radical Constructivism: A Way Of Knowing And Learning. London: Falmer Press.
Hebb, D.O.: 1949, The Organization of Behavior; A Neuropsychological Theory. New York: Wiley.
Heiden, U.a.d.: 1992, Selbstorganisation in dynamischen Systemen. In W. Krohn and G. Küppers (eds.), Emergenz: die Entstehung von Ordnung, Organisation und Bedeutung. Frankfurt/M.: Suhrkamp, 57–88.
Hertz, J., A. Krogh and R.G. Palmer: 1991, Introduction to the Theory of Neural Computation, Volume 1 of Santa Fe Institute Studies In The Sciences Of Complexity. Lecture Notes. Redwood City, Ca: Addison-Wesley.
Hinton, G.E.: 1987, Connectionist Learning Procedures. Technical Report CMUCS-87-115, Carnegie-Mellon University, Pittburgh, PA.
Holland, J.H.: 1975, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Ann Arbor: University of Michigan Press.
Horgan, T. and J. Tienson: 1996, Connectionism and the Philosophy of Psychology. Cambridge, MA: MIT Press.
Hubel, D.H.: 1988, Eye, Brain, And Vision. New York: Freeman.
Hubel, D.H. and T.N. Wiesel: 1968, Receptive Fields and Functional Architecture of Monkey Striate Cortex. Journal of Physiology 195: 215–243.
Jessel, T.M.: 1991, Neuronal Survival and Synapse Formation. In E.R. Kandel, J.H. Schwartz and T.M. Jessel (eds.), Principles Of Neural Science (3rd ed.). New York: Elsevier, 929–944.
Kandel, E.R., J.H. Schwartz and T.M. Jessel (eds.): 1991, Principles of Neural Science (3rd ed.). New York: Elsevier.
Kosso, P.: 1992, Reading the Book of Nature. An Introduction to the Philosophy of Science. Cambridge: Cambridge University Press.
Kuhn, T.S.: 1970, The Structure of Scientific Revolutions (2nd ed.). Chicago: University of Chicago Press.
Langton, C.G. (ed.): 1989, Artificial Life. Redwood City, CA: Addison-Wesley.
Langton, C.G. (ed.): 1994, Artificial Life III. Redwood City, CA: Addison-Wesley.
Langton, C.G. (ed.): 1995, Artificial Life. An Introduction. Cambridge, MA: MIT Press.
Maturana, H.R.: 1991, Science and Daily Life: The Ontology of Scientific Explanations. In F. Steier (ed.), Research and reflexivity. London, Newbury Park, CA: SAGE Publishers, 30–52.
Maturana, H.R. (ed.): 1998, Biologie der Realität. Frankfurt/M.: Suhrkamp.
Maturana, H.R. and F.J. Varela (eds.): 1980, Autopoiesis and Cognition: The Realization of the Living, Volume 42 of Boston Studies in the Philosophy of Science. Dordrecht, Boston: D. Reidel Pub. Co.
Miller, G., P. Todd and S. Hedge: 1989, Designing Neural Networks Using Genetic Algorithms. In J.D. Schaffer (ed.), Proceedings of the Third International Conference on Genetic Algorithms. San Mateo, CA: M. Kaufmann Pub.
Mitchell, M. and S. Forrest: 1994, Genetic Algorithms and Artificial Life. Artficial Life 1(3): 267–291.
Newell, A.: 1980, Physical Symbol Systems. Cognitive Science 4: 135–183.
Newell, A. and H.A. Simon: 1976, Computer Science as Empirical Inquiry: Symbols and Search. Communications of the Assoc. for Computing Machinery (ACM) 19(3): 113–126 (reprinted in M. Boden (ed.), The Philosophy of Artificial Intelligence, Oxford University Press, 1990; in German in D. Münch (ed.), Kognitionswissenschaft, Suhrkamp, 1992).
Peschl, M.F.: 1994a, Embodiment of Knowledge in the Sensory System and its Contribution to Sensorimotor Integration. The Role of Sensors in Representational and Epistemological Issues. In P. Gaussier And J.D. Nicoud (eds.), From Perception to Action Conference. Los Alamitos, CA: IEEE Society Press, 444–447.
Peschl, M.F.: 1994b, Repräsentation und Konstruktion. Kognitions-und neuroinformtische Konzepte als Grundlage einer naturalisierten Epistemologie und Wissenschaftstheorie. Braunschweig/Wiesbaden: Vieweg.
Peschl, M.F.: 1997, The Representational Relation Between Environmental Structures and Neural Systems: Autonomy and Environmental Dependency in Neural Knowledge Representation. Nonlinear Dynamics, Psychology, and Life Sciences 1(2): 99–121.
Port, R. and T.v. Gelder (eds.): 1995, Mind as Motion: Explorations in theDynamics of Cognition. Cambridge, MA: MIT Press.
Roth, G.: 1992, Kognition: die Entstehung von Bedeutung im Gehirn. In W. Krohn and G. Küppers (eds.), Emergenz: die Entstehung von Ordnung, Organisation und Bedeutung. Frankfurt/M.: Suhrkamp, 104–132.
Roth, G.: 1994, Das Gehirn und seine Wirklichkeit. Kognitive Neurobiologie und ihre Philosophischen Konsequenzen. Frankfurt/M.: Suhrkamp.
Rumelhart, D.E. and J.L. McClelland (eds.): 1986, Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Foundations, Volume I. Cambridge, MA: MIT Press.
Schmidt, S.J.: 1998, Die Zähmung des Blicks. Konstruktivismus – Empirie – Wissenschaft. Frankfurt/M.: Suhrkamp.
Schwartz, E.L. (ed.): 1990, Computational Neuroscience. Cambridge, MA: MIT Press.
Sejnowski, T.J., C. Koch and P.S. Churchland: 1988, Computational Neuroscience. Science 241(4871): 1299–1306.
Steels, L.: 1995, The Artificial Life Roots of Artificial Intelligence. In C.G. Langton (ed.), Artificial Life. An Introduction. Cambridge, MA: MIT Press, 75–110.
Steier, F. (ed.): 1991, Research and Reflexivity. London; Newbury Park, CA: SAGE Publishers.
Thagard, P.: 1988, Computational Philosophy of Science. Cambridge, MA: MIT Press.
Varela, F.J., E. Thompson and E. Rosch (1991). The Embodied Mind: Cognitive Science and Human Experience. Cambridge, MA: MIT Press.
Wiener, N.: 1948, Cybernetic. Control and Communication in the Animal and the Machine. New York: Wiley.
Winston, P.H.: 1992, Artificial Intelligence (3rd ed.). Reading, MA: Addison-Wesley.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Peschl, M.F. Constructivism, Cognition, and Science – An Investigation of Its Links and Possible Shortcomings. Foundations of Science 6, 125–161 (2001). https://doi.org/10.1023/A:1011390200250
Issue Date:
DOI: https://doi.org/10.1023/A:1011390200250