Swarm Intelligence and Robotics
Markov chains are mathematical systems that undergo transitions from one state to another based on certain probabilistic rules. They are characterized by the property that the future state depends only on the current state and not on the sequence of events that preceded it, which is known as the Markov property. This property makes them particularly useful in modeling stochastic processes, such as self-organized task allocation, where agents or robots must make decisions based on their current state and the surrounding environment.
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