Deep Reinforcement Learning for Autonomous Systems: Advances in Navigation and Decision-Making
Keywords:
Deep Reinforcement Learning, Autonomous Systems, Decision-MakingAbstract
Deep reinforcement learning (DRL) has emerged as a powerful paradigm for training autonomous systems to navigate and make decisions in complex environments. recent advances in DRL algorithms and their application to autonomous navigation and decision-making tasks. DRL combines deep learning techniques with reinforcement learning principles to enable agents to learn optimal policies through interaction with their environment. By leveraging neural networks to approximate value functions and policy functions, DRL algorithms can effectively handle high-dimensional state and action spaces, making them well-suited for real-world autonomous systems.
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