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A novel Dual Q–Adaptive Weighting model that balances reward and cost through a primal–dual learning mechanism is proposed and achieves the highest route accuracy of 78.66%, outperforming Double Q-Learning, Q-Learning, and traditional A* and Dijkstra algorithms.
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