Lesson 10: Cluster control and game confrontation
The concept of clusters traces its roots to biological research, where the French zoologist Grasse first introduced the principle of Stigmergy based on the nesting behavior of termites. He posited that this mechanism enables individuals to engage in complex, seemingly intelligent activities without centralized planning or direct communication—a seminal idea that marked the inception of autonomous cluster concepts into human understanding and gradual development.
This notion has evolved and expanded from biological systems to Multi-Agent Systems (MAS). A Multi-Agent System refers to an environment where multiple agents operate simultaneously, each needing to compete or collaborate with others while interacting within their shared environment. When a MAS scales up to tackle highly complex tasks, it is often referred to as a cluster. Cluster control primarily focuses on the consistency problem, aiming to leverage distributed coordination control algorithms to ensure that the states or outputs of all entities within the "network" achieve a specific level of harmony.
A distributed coordinated control algorithm constitutes a set of local rules that, when implemented, give rise to coherent global behavior without requiring central oversight. In the context of RflySim platform's UAV cluster simulation, this principle serves as the core foundation. The platform simulates scenarios where numerous unmanned aerial vehicles (UAVs) form a cluster, necessitating the application of distributed coordination strategies to perform intricate missions effectively and efficiently.
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Issue 8: Communication protocols and cluster networking & cluster control and game confrontation (Part 1)
Issue 8: Communication protocols and cluster networking & cluster control and game confrontation (Part 2)
Issue 8: Communication protocols and cluster networking & cluster control and game confrontation (Part 3)