The invention discloses a converged communication
system and method for emergency command and dispatch, and the method comprises the following steps: S1, constructing a converged communication network environment, and configuring a self-adaptive network switching module; s2, collecting and analyzing
task demand data in an emergency scene, and generating a
task demand prediction matrix; s3, generating a task scheduling rule; s4, acquiring current network state data, and generating task scheduling constraint conditions; s5, constructing and training a multi-agent
reinforcement learning model; s6, optimizing a communication path
decision strategy and a task scheduling rule by adopting a self-adaptive multi-objective optimization
algorithm; s7, calculating an optimal communication path, and executing intelligent adaptive network switching; and S8, collecting task execution feedback data, and adjusting training parameters of the multi-agent
reinforcement learning model. According to the method, multi-agent
reinforcement learning and dynamic entropy regulation and control optimization are combined, emergency communication task scheduling and path optimization are achieved, and the method has the advantages of being high in adaptability, high in communication stability and excellent in task execution efficiency.