Emergence of a snake-like structure in mobile distributed agents: an exploratory agent-based modeling approach

Area of Science:

• Robotics
• Artificial Intelligence
• Complex Systems

Background:

• Natural snake bodies exhibit resilience and adaptability due to numerous components.
• Current artificial snake-like structures use fewer components, limiting their flexibility and requiring intensive computation.
• Existing animations often lack life-like resilience and adaptive capabilities.

Purpose of the Study:

• To address limitations in modeling and animating snake-like structures.
• To propose a novel agent-based, self-organizing algorithm for dynamic and resilient artificial systems.
• To explore applications in animation and robotics.

Main Methods:

• Development of an agent-based, self-organizing algorithm.
• Simulation experiments to evaluate the algorithm's effectiveness and resilience.
• Exploratory agent-based modeling (EABM) for complex adaptive systems.

Main Results:

• The proposed algorithm generates emergent, resilient dynamic structures.
• Minimal inter-agent communication is required for the system's operation.
• Simulations confirm the approach's effectiveness and resilience.

Conclusions:

• The algorithm provides a solution for creating life-like, resilient snake-like animations.
• Potential applications include developing complex, autonomous, and evolvable robots.
• Highlights the utility of EABM in engineering artificial complex adaptive systems.