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The first step of the proposed method, is generating the distance matrix. We use A Star to find the shortest path between each of the 20 cities. Since we are using a grid map, so the distance is calculated by the Manhattan distance. We have 128K data, so there are 128K distance matrix total. Then the next step is to find the best path from the distance matrix. We consider to use Heuristic Algorithm and Reinforcement Learning to achieve this goal. Genetic Algorithm and Simulated Annealing Algorithm are two famous Heuristic Algorithm to process these problems. Thus we use these two algorithm in our method. Then we design an Actor-Critic Structure reinforcement learning model.
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IEEE/ICACT20230128 Slide.07
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