David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Cognitive Science 35 (3):444-479 (2011)
We define a mathematical formalism based on the concept of an ‘‘open dynamical system” and show how it can be used to model embodied cognition. This formalism extends classical dynamical systems theory by distinguishing a ‘‘total system’’ (which models an agent in an environment) and an ‘‘agent system’’ (which models an agent by itself), and it includes tools for analyzing the collections of overlapping paths that occur in an embedded agent's state space. To illustrate the way this formalism can be applied, several neural network models are embedded in a simple model environment. Such phenomena as masking, perceptual ambiguity, and priming are then observed. We also use this formalism to reinterpret examples from the embodiment literature, arguing that it provides for a more thorough analysis of the relevant phenomena
|Keywords||Representation Embodied cognition Dynamical systems Neural networks|
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References found in this work BETA
Randall D. Beer (2000). Dynamical Approaches to Cognitive Science. Trends in Cognitive Sciences 4 (3):91-99.
Andy Clark (2009). Spreading the Joy? Why the Machinery of Consciousness is (Probably) Still in the Head. Mind 118 (472):963-993.
Andy Clark (2008). Supersizing the Mind: Embodiment, Action, and Cognitive Extension. Oxford University Press.
Rick Dale, Eric Dietrich & Anthony Chemero (2009). Explanatory Pluralism in Cognitive Science. Cognitive Science 33 (2):739-742.
Citations of this work BETA
Tomer Fekete & Shimon Edelman (2011). Towards a Computational Theory of Experience. Consciousness and Cognition 20 (3):807-827.
Whitney Tabor, Pyeong W. Cho & Harry Dankowicz (2013). Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task. Cognitive Science 37 (7):1193-1227.
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