Embodied Dyadic Interaction Increases Complexity of Neural Dynamics: A Minimal Agent-Based Simulation Model.
Madhavun Candadai1,2, Matt Setzler1,2, Eduardo J Izquierdo1,2
1Program in Cognitive Science, Indiana University, Bloomington, IN, United States.
Frontiers in Psychology
|April 6, 2019
Summary
Social interaction can increase an individual
Area of Science:
- Cognitive Science
- Artificial Intelligence
- Robotics
- Embodied Cognition
Background:
- Social interaction is central to embodied and enactive cognitive science.
- Traditional cognitive science focused on internal neural activity, neglecting interaction's role.
- The impact of social interaction on individual complexity is poorly understood.
Purpose of the Study:
- To investigate if social interaction enhances individual complexity.
- To explore the behavioral and neural dynamics during social interaction.
- To provide a proof of concept for social interaction augmenting complexity.
Main Methods:
- Artificial evolution of simulated mobile robot pairs.
- Evolving robots for increased neural complexity.
- Analyzing neural controller dynamics during interaction and isolation.
- Testing evolved strategies against unresponsive 'ghost' partners.
Main Results:
- Evolved strategies leveraged interaction capabilities.
- Neural controllers showed higher-dimensional dynamics during social interaction compared to isolation.
- The complexity increase depended on mutual co-regulation, not just the presence of another agent.
Conclusions:
- Social interaction can increase an individual's internal complexity.
- Mutually responsive co-regulation is key to this complexity augmentation.
- Findings support the role of social interaction in enhancing cognitive processes.
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