David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
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
James J. Gibson (1979). The Ecological Approach to Visual Perception. Houghton Mifflin.
Andy Clark (2008). Supersizing the Mind: Embodiment, Action, and Cognitive Extension. Oxford University Press.
Alva Noë (2005). Action in Perception. The MIT Press.
Citations of this work BETA
Randall D. Beer & Paul L. Williams (2015). Information Processing and Dynamics in Minimally Cognitive Agents. Cognitive Science 39 (1):1-38.
Tomer Fekete & Shimon Edelman (2011). Towards a Computational Theory of Experience. Consciousness and Cognition 20 (3):807-827.
Jeff Yoshimi & David W. Vinson (2015). Extending Gurwitsch’s Field Theory of Consciousness. Consciousness and Cognition 34:104-123.
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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