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How Morphological Computation Shapes Integrated Information in Embodied Agents
Carlotta Langer1,2, Nihat Ay1,2,3,4
1Hamburg University of Technology, Hamburg, Germany.
Frontiers in Psychology
|December 16, 2021
Summary
Integrated Information Theory quantifies consciousness in neural networks. Embodied agents show an inverse relationship between morphological computation and brain information integration.
Area of Science:
- Cognitive Science
- Neuroscience
- Artificial Intelligence
Background:
- Integrated Information Theory (IIT) offers a quantitative framework for consciousness.
- Embodied agents, controlled by neural networks, interact dynamically with their environment.
- This interaction involves morphological computation in action and integrated information in the brain.
Purpose of the Study:
- To examine information flows within and between an agent's body, brain, and environment.
- To relate different information flow dynamics.
- To investigate the interplay between morphological computation and integrated information.
Main Methods:
- Utilized a 'planning as inference' method with an information-geometric EM-algorithm to determine optimal policies for goal-directed behavior.
- Calculated morphological computation and integrated information based on these optimal policies.
- Analyzed the dynamics of these measures under varying morphological conditions.
Main Results:
- Identified an antagonistic relationship between morphological computation and integrated information.
- Demonstrated that increased morphological computation correlates with decreased information integration in the brain.
- Highlighted the necessity of measuring information flow to and from the brain to understand its influence on agent behavior.
Conclusions:
- The study provides a framework for analyzing information flow in embodied agents.
- Findings suggest a trade-off between externalizing computation (morphological computation) and internal processing (information integration).
- Future research should focus on bidirectional information flow to fully grasp brain-environment-body interactions.
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