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Outsourcing Control Requires Control Complexity
Carlotta Langer1, Nihat Ay2,3,4
1Hamurg University of Technology, Institute for Data Science Foundations. carlotta.langer@tuhh.de.
Artificial Life
|June 24, 2024
Summary
Embodied agents use sensorimotor loops to interact with their environment. Understanding environmental dynamics is key, and increased controller complexity can enhance this interaction, even with well-adapted morphology.
Area of Science:
- Robotics
- Artificial Intelligence
- Information Theory
Background:
- Embodied agents interact with their environment through sensorimotor loops.
- Information-theoretic measures quantify these interactions, including morphological computation.
- Controller complexity is examined in relation to integrated information theory.
Purpose of the Study:
- To analyze the interaction between embodied agents and their environment.
- To quantify information flow within the agent-environment system.
- To investigate the role of controller complexity and environmental understanding.
Main Methods:
- Modeling agent-environment interactions using the sensorimotor loop.
- Applying information-theoretic measures to quantify information flow.
- Utilizing simulated agents in an experimental setting.
Main Results:
- Morphological adaptation can reduce controller complexity.
- Agents must first understand environmental dynamics for effective interaction.
- Increased controller complexity can improve agent-environment interaction.
Conclusions:
- Agent-environment interaction is a dynamic interplay influenced by both morphology and controller.
- Understanding environmental dynamics is a prerequisite for effective morphological computation.
- Controller complexity plays a crucial role in facilitating sophisticated agent-environment interactions.
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