A Study Method of Bitcoin Mining Pool Attack Strategy Based on Stochastic Game Reinforcement Learning
A technology of enhanced learning and policy learning, applied in machine learning, digital transmission systems, instruments, etc.
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[0078] Figure 4 shows a simplified example of the process of finding an approximate Nash equilibrium to obtain an approximate optimal strategy pair for this iteration. The figure shows the payoff matrix when the two mining pools take different actions. Assuming ò = 0.01, then the approximate optimal action in state s eventually converges to last pair best policy pair in current state The action selection strategy is updated.
[0079] Step 6, according to Update the state value V of mining pool 1 in state s 1 t+1 (s); according to Update the state value of mining pool 2 in state s Where δ∈[0,1) is the learning rate of the mining pool, and in the tth iteration, the size is δ decreases as the number of iterations increases, which is helpful for the convergence of the algorithm in the later stage.
[0080] The concrete implementation process of embodiment is as follows:
[0081] The state value is the benefit in different states. Suppose the initial state of mini...
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