A neural network's predicted guideline and region are used as a reward function and Q-table initializer, cutting Q-learning convergence steps by about 90% in grid path planning simulations.
Path planning of autonomous mobile robot in comprehensive unknown environm ent using deep reinforcement learning,
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Neural-Network-Driven Reward Prediction as a Heuristic: Advancing Q-Learning for Mobile Robot Path Planning
A neural network's predicted guideline and region are used as a reward function and Q-table initializer, cutting Q-learning convergence steps by about 90% in grid path planning simulations.