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Embodied cognitive morphogenesis as a route to intelligent systems
Bradly Alicea1,2, Richard Gordon3, Jesse Parent2
1OpenWorm Foundation, Boston, MA, USA.
Interface Focus
|April 17, 2023
Summary
Embodied cognitive morphogenesis unites embryology and cognition, explaining how development and environment create intelligent behaviors. This framework models autonomous systems using symmetry breaking and information processing for bioinspired agent design.
Area of Science:
- Developmental Biology
- Cognitive Science
- Systems Biology
Background:
- Embryology emphasizes gene expression and cell mechanics for development.
- Embodied cognition highlights organism-environment interaction for intelligence.
- These views are often considered separate, limiting a holistic understanding of biological systems.
Purpose of the Study:
- To integrate embryological and cognitive perspectives into a unified framework: embodied cognitive morphogenesis.
- To explore how morphogenetic symmetry breaking leads to specialized subsystems and autonomous behaviors.
- To identify key properties (acquisition, generativity, transformation) of these developmental systems.
Main Methods:
- Modeling embodied cognitive morphogenesis using a generic organismal agent.
- Utilizing computational models like tensegrity networks, differentiation trees, and embodied hypernetworks.
- Analyzing symmetry-breaking events within developmental time.
Main Results:
- Demonstrated how morphogenetic processes generate phenotypic asymmetry and information processing subsystems.
- Identified acquisition, generativity, and transformation as key properties of emergent autonomous behaviors.
- Linked embodied cognitive morphogenesis to concepts like modularity, homeostasis, and 4E cognition.
Conclusions:
- Embodied cognitive morphogenesis offers a novel framework for understanding the development of complex organisms and intelligent behavior.
- Autonomous developmental systems can be viewed as a process of connectogenesis, integrating emergent phenotypes.
- This approach is valuable for analyzing biological systems and designing bioinspired computational agents.
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