On the Proper Treatment of Dynamics in Cognitive Science.
Behavior
Dynamics
Embodiment
Situatedness
Theoretical framework
Journal
Topics in cognitive science
ISSN: 1756-8765
Titre abrégé: Top Cogn Sci
Pays: United States
ID NLM: 101506764
Informations de publication
Date de publication:
02 Aug 2023
02 Aug 2023
Historique:
revised:
25
07
2023
received:
28
02
2023
accepted:
25
07
2023
medline:
2
8
2023
pubmed:
2
8
2023
entrez:
2
8
2023
Statut:
aheadofprint
Résumé
This essay examines the relevance of dynamical ideas for cognitive science. On its own, the mere mathematical idea of a dynamical system is too weak to serve as a scientific theory of anything, and dynamical approaches within cognitive science are too rich and varied to be subsumed under a single "dynamical hypothesis." Instead, after first attempting to dissect the different notions of "dynamics" and "cognition" at play, a more specific theoretical framework for cognitive science broadly construed is sketched. This framework draws upon not only dynamical ideas, but also such contemporaneous perspectives as situatedness, embodiment, ecological psychology, enaction, neuroethology/neuroscience, artificial life, and biogenic approaches. The paper ends with some methodological suggestions for pursuing this theoretical framework.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2023 Cognitive Science Society LLC.
Références
Agmon, E., & Beer, R. D. (2014). The dynamics of action switching in an evolved agent. Adaptive Behavior, 22, 3-20.
Aizawa, K. (2014). What is this cognition that is supposed to be embodied? Philosophical Psychology, 28, 755-775.
Allen, C. (2017). On (not) defining cognition. Synthese, 194, 4233-4249.
Andrews, K., & Monsó, S. (2021). Animal cognition. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (Spring 2021 edition). https://plato.stanford.edu/
Ashby, W. R. (1952/1960). Design for a brain: The origin of adaptive behavior. Wiley & Sons.
Barnes, J. (1982). The natural philosophy of Heraclitus. In J. Barnes (Ed.). The presocratic philosophers (pp. 43-62). London: Routledge Taylor & Francis.
Barack, D. L. (2019). Mental machines. Biology and Philosophy, 34, 63.
Barrett, L. (2012). Why behaviorism isn't satanism. In J. Vonk & T. K. Shackelford (Eds.), The Oxford handbook of comparative evolutionary psychology (pp. 17-38). Oxford University Press.
Bechtel, W. (1998). Representations and cognitive explanations: Assessing the dynamicist's challenge in cognitive science. Cognitive Science, 22, 295-318.
Beer, R. D. (1990). Intelligence as adaptive behavior: Experiments in computational neuroethology. Academic Press.
Beer, R. D. (1995a). A dynamical systems perspective on agent−environment interaction. Artificial Intelligence, 72, 173-215.
Beer, R. D. (1995b). Computational and dynamical languages for autonomous agents. In R. Port & T. van Gelder (Eds.), Mind as motion: Explorations in the dynamics of cognition (pp. 121-147). MIT Press.
Beer, R. D. (1996). Toward the evolution of dynamical neural networks for minimally cognitive behavior. In P. Maes, M. Mataric, J. Meyer, J. Pollack, & S. Wilson (Eds.), From Animals to Animats 4: Proceedings of the 4th International Conference on Simulation of Adaptive Behavior (pp. 421-429). MIT Press.
Beer, R. D. (1997). The dynamics of adaptive behavior: A research program. Robotics and Autonomous Systems, 20, 257-299.
Beer, R. D. (1998). Framing the debate between computational and dynamical approaches to cognitive science. Behavioral and Brain Sciences, 21(5), 630.
Beer, R. D. (2000). Dynamical approaches to cognitive science. Trends in Cognitive Sciences, 4(3), 91-99.
Beer, R. D. (2003a). The dynamics of active categorical perception in an evolved model agent. Adaptive Behavior, 11, 209-243.
Beer, R. D. (2003b). Arches and stones in cognitive architecture. Adaptive Behavior, 11, 299-305.
Beer, R. D., & Di Paolo, E. A. (2023). The theoretical foundations of enaction: Precariousness. BioSystems, 223, 104823.
Beer, R. D., & Gallagher, J. G. (1992). Evolving dynamical neural networks for adaptive behavior. Adaptive Behavior, 1, 91-122.
Beer, R. D., & Williams, P. L. (2009). Animals and animats: Why not both iguanas? Adaptive Behavior, 17, 296-302.
Beer, R. D., & Williams, P. L. (2015). Information processing and dynamics in minimally cognitive agents. Cognitive Science, 39, 1-38.
Campos, B., Canela, J., & Vindel, P. (2022). Dynamics of Newton-like root finding methods. Numerical Algorithms, 93, 1453-1480.
Chemero, A. (2011). Radical embodied cognitive science. MIT Press.
Chiel, H. J., & Beer, R. D. (1997). The brain has a body: Adaptive behavior emerges from interactions of nervous system, body and environment. Trends in Neurosciences, 20, 553-557.
Clancey, W. J. (1997). Situated cognition: On human knowledge and computer representations. Cambridge University Press.
Clark, A., & Toribio, J. (1994). Doing without representing? Synthese, 101, 401-431.
Craver, C., & Tabery, J. (2019). Mechanisms in science. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (Spring 2019 edition).
Diacu, F., & Holmes, P. (1996). Celestial encounters: The origins of chaos and stability. Princeton University Press.
Edelman, S. (2003). But will it scale up? Not without representations. Adaptive Behavior, 11, 273-275.
Eliasmith, C. (1996). The third contender: A critical examination of the dynamicist theory of cognition. Philosophical Psychology, 9(4), 441-463.
Eliasmith, C. (1997). Computation and dynamical models of mind. Minds and Machines, 7, 531-541.
Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14, 179-211.
Favela, L. H. (2021). The dynamical renaissance in neuroscience. Synthese, 199(1), 2103-2127.
Giunti, M. (1997). Computation, dynamics, and cognition. Oxford University Press.
Gleick, J. (1987). Chaos: Making a new science. Viking.
Gomez-Marin, A., & Ghazanfar, A. A. (2019). The life of behavior. Neuron, 104, 25-36.
Grossberg, S. (1988). Neural networks and natural intelligence. Cambridge, MA: MIT Press.
Grush, R. (1997). Review of Port and van Gelder's mind as motion. Philosophical Psychology, 10, 233-242.
Grush, R. (2003). In defense of some ‘Cartesian’ assumptions concerning the brain and its operation. Biology and Philosophy, 18, 53-93.
Haken, H. (1983). Synergetics: An introduction. Springer.
Hao, B., & Zheng, W. (2018). Applied symbolic dynamics and chaos (2nd edition). World Scientific.
Izquierdo, E., Harvey, I., & Beer, R. D. (2008). Associative learning on a continuum in evolved dynamical neural networks. Adaptive Behavior, 16, 361-384.
Keijzer, F. (2021). Demarcating cognition: The cognitive life sciences. Synthese, 198(Suppl1), S137-S157.
Kelso, J. A. S. (1995). Dynamic patterns: The self-organization of brain and behavior. Cambridge, MA: MIT Press.
Krakauer, J. W., Ghazanfar, A. A., Gomez-Marin, A., MaIver, M. A., & Poeppel, D. (2017). Neuroscience needs behavior: Correcting a reductionist bias. Neuron, 93, 480-490.
Kugler, P. N., & Turvey, M. T. (1987). Information, natural law, and the self-assembly of rhythmic movement. Hillsdale, NJ: Lawrence Erlbaum.
Kuznetsov, Y. A. (2004). Elements of applied bifurcation theory (3rd edition). New York: Springer.
Levin, M., Keijzer, F., Lyon, P., & Arendt, D. (2021). Uncovering cognitive similarities and differences, conservation and innovation. Philosophical Transactions of the Royal Society B: Biological Sciences, 376, 20200458
Luce, R. D. (1995). Four tensions concerning mathematical modeling in psychology. Annual Review of Psychology, 46, 1-26.
Lyon, P. (2006). The biogenic approach to cognition. Cognitive Processing, 7(1), 11-29.
Lyon, P., Keijzer, F., Arendt, D., & Levin, M. (2021). Reframing cognition: Getting down to biological basics. Philosophical Transactions of the Royal Society B: Biological Sciences, 376, 20190750.
Maturana, H. R., & Varela, F. J. (1980). Autopoiesis and cognition: The realization of the living. D. Reidel Publishing Company.
Phattanasri, P., Chiel, H. J., & Beer, R. D. (2007). The dynamics of associative learning in evolved model circuits. Adaptive Behavior, 15, 377-396.
Piccinini, G. (2015). Physical computation: A mechanistic account. Oxford University Press.
Pollack, J. B. (1991). The induction of dynamical recognizers. Machine Learning, 7, 227-252.
Port, R. F., & van Gelder, T. (1995). Mind as motion: Explorations in the dynamics of cognition. Cambridge, MA: MIT Press.
Rupert, R. D. (2009). Cognitive systems and the extended mind. Oxford University Press.
Schöner, G., & Kelso, J. A. S. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239, 1513-1520.
Schöner, G., Spencer, J. P., & the DFT Research Group. (2016). Dynamic thinking: A primer on dynamic field theory. Oxford University Press.
Shapiro, L. (2019). Embodied cognition (2nd edition). Routledge.
Skarda, C. A., & Freeman, W. J. (1987). How brains make chaos in order to make sense of the world. Behavioral and Brain Sciences, 10(2), 161-195.
Slocum, A. C., Downey, D. C., & Beer, R. D. (2000). Further experiments in the evolution of minimally cognitive behavior: From perceiving affordances to selective attention. In J. Meyer, A. Berthoz, D. Floreano, H. Roitblat, & S. Wilson (Eds.), From Animals to Animats 6: Proceedings of the 6th International Conference on Simulation of Adaptive Behavior (pp. 430-439). MIT Press.
Smolensky, P. (1988). On the proper treatment of connectionism. Behavioral and Brain Sciences, 11, 1-74.
Spivey, M. (2008). The continuity of mind. Oxford University Press.
Thelen, E., & Smith, L. B. (1994). A dynamic systems approach to the development of cognition and action. Cambridge, MA: MIT Press.
Thelen, E., Schöner, G., Scheier, C., & Smith, L. B. (2001). The dynamics of embodiment: A field theory of infant perseverative reaching. Behavioral and Brain Sciences, 24(1), 70-80.
Thompson, E. (2007). Mind in life: Biology, phenomenology, and the sciences of the mind. MIT Press.
van Gelder, T. (1995). What might cognition be, if not computation? Journal of Philosophy, 92(7), 345-381.
van Gelder, T. (1998). The dynamical hypothesis in cognitive science. Behavioral and Brain Sciences, 21(5), 615-628.
Van Leeuwen, M. (2005). Questions for the dynamicist: The use of dynamical systems theory in the philosophy of cognition. Minds and Machines, 15, 271-333.
Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind: Cognitive science and human experience. MIT Press
Warren, W. H. (2006). The dynamics of perception and action. Psychological Review, 113(2), 358-389.
Webb, B. (2009). Animals vs. animats: Or why not model the real iguana? Adaptive Behavior, 17, 269-286.
Wiggins, S. (2003). Introduction to applied nonlinear dynamical systems and chaos (2nd edition). Springer.
Williams, P. L., Beer, R. D., & Gasser, M. (2008a). An embodied dynamical approach to relational categorization. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 223-228).
Williams, P. L., Beer, R. D., & Gasser, M. (2008b). Evolving referential communication in embodied dynamical agents. In S. Bullock, J. Noble, R. Watson, & M. A. Bedau (Eds.), Artificial Life XI: Proceedings of the 11th International Conference on the Simulation and Synthesis of Living Systems (pp. 702-709). MIT Press.
Williams, P. L., & Beer, R. D. (2013). Environmental feedback drives multiple behaviors from the same neural circuit. In P. Lio, O. Miglino, G. Nicosia, S. Nolfi, & M. Pavone (Eds.), Advances in Artificial Life: ECAL 2013 (pp. 268-275).
Yamauchi, B., & Beer, R. D. (1994). Sequential behavior and learning in evolved dynamical neural networks. Adaptive Behavior, 2, 219-246.
Zednik, C. (2011). The nature of dynamical explanation. Philosophy of Science, 78(2), 238-263.