Improved Double Deep Q Network Algorithm Based on Average Q-Value Estimation and Reward Redistribution for Robot Path Planning
Source abstract
Abstract
By integrating deep neural networks with reinforcement learning, the Double Deep Q Network (DDQN) algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning of m... | Find, read and cite all the research you need on Tech Science Press
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Research context
OpenAlex topics: Robotic Path Planning Algorithms · Robotics and Automated Systems
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References (35)
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