Based on any of the materials in Modules/Weeks 1-6, describe the key similarities and differences between the dynamical systems approach to cognition (i.e., “mind as a Watt governor”) and the CRUM approach to cognition (i.e., “mind as computation).” In your description, be sure to include the weaknesses of CRUM and discuss the advantages of dynamical systems.
Cognitive psychology has witnessed the emergence of various theoretical frameworks aimed at understanding the workings of the human mind. Two prominent approaches in this regard are the dynamical systems approach, often described as “mind as a Watt governor,” and the Computational Representational Understanding of Mind (CRUM), known as “mind as computation.” In this essay, we will explore the key similarities and differences between these two approaches, while also highlighting the weaknesses of CRUM and the advantages of the dynamical systems perspective.
The dynamical systems approach views cognition as a complex, self-organizing system that emerges from the interactions of various components. Key features of this approach include:
Non-linearity: Cognitive processes are considered non-linear and dynamic, with outcomes emerging from the interaction of multiple elements.
Self-Organization: Cognitive systems self-organize, adapting to environmental changes and allowing for flexibility in behavior.
Embodiment: Cognitive processes are intricately linked with the body and its interactions with the environment.
Contextual Sensitivity: Cognitive processes are context-dependent and sensitive to changes in the environment.
In contrast, the CRUM approach views cognition as a form of computation, akin to a computer processing information. Key features of this approach include:
Symbolic Representation: Cognitive processes are represented symbolically, with mental operations resembling computation.
Modularity: The mind is often conceived as a modular system, with specialized modules for various cognitive functions.
Digital Processing: Cognitive processes are seen as digital in nature, involving discrete symbols and rules.
Top-Down Processing: The CRUM approach often incorporates top-down processing, where higher-level cognitive functions guide lower-level processes.
Cognition as Information Processing: Both approaches share the overarching view that cognition involves processing information in some form.
Complexity: They acknowledge the complexity of cognitive processes, albeit with different explanations.
Nature of Computation: While CRUM views cognition as symbolic computation, the dynamical systems approach emphasizes the dynamic and non-linear nature of cognitive processes.
Embodiment: The dynamical systems approach highlights the role of embodiment, emphasizing the interaction between the body and the environment, whereas CRUM tends to focus on abstract symbol manipulation.
Simplistic Representation: CRUM’s reliance on symbolic representation oversimplifies the richness and complexity of human cognition. It struggles to capture the nuanced and context-dependent nature of cognitive processes.
Modularity Oversimplification: The modular view of cognition in CRUM can lead to an oversimplification of how different cognitive processes interact. It may not adequately address the dynamic nature of cognition.
Flexibility and Adaptability: The dynamical systems approach excels in explaining the flexibility and adaptability of cognitive systems in response to changing contexts and environments.
Emphasis on Embodiment: By considering the role of embodiment, this approach provides a more holistic understanding of how cognition emerges from the interaction between the mind, body, and environment.
Non-Linearity: Recognizing the non-linear nature of cognitive processes allows for a better explanation of phenomena such as creativity and problem-solving, which are not well-addressed by CRUM.
In summary, the dynamical systems approach and CRUM represent two distinct perspectives on cognition. While CRUM relies on symbolic computation and modularity, the dynamical systems approach emphasizes non-linearity, embodiment, and context sensitivity. CRUM’s weaknesses lie in its oversimplification and inability to account for the dynamic nature of cognition, while the dynamical systems approach offers advantages in explaining adaptability and the embodied nature of cognitive processes. Ultimately, the choice between these approaches depends on the research question and the complexity of the cognitive phenomena under investigation.
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