A 3D Crowd Exploration Method Based on Multi-Head Attention Asynchronous Reinforcement Learning
A technology of reinforcement learning and attention, applied in neural learning methods, design optimization/simulation, instruments, etc., can solve problems such as insufficient exploration, low sample utilization rate, slow acquisition speed, etc., to solve the problem of insufficient exploration, good Sensitive data acquisition effect, strong noise interference effect
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[0060] The content of the present invention will be further described in detail below in conjunction with the accompanying drawings of the description. Such as figure 1 Shown, method of the present invention comprises the following steps:
[0061] Step 1. The command center initializes the benchmark exploration strategy and environmental parameters, and the UAV group performs data collection according to the changes in the perceived environment:
[0062] Step 1.1. The main process of the command center sets up a shared sample reuse cache and initializes a benchmark exploration strategy, and establishes an empty shared sample reuse cache and initializes a benchmark exploration strategy on the command center in the 3D mobile crowd sensing scene;
[0063] Step 1.2, establish multiple sub-processes, synchronize the exploration strategies of the sub-processes and initialize the environmental parameters in each sub-process. The environmental parameters include the position of the U...
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