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最全自动驾驶技术架构和综述_李博Garvin的专栏-CSDN博客

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New algorithm makes it easier for computers to solve decision making problems

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IMAGE: Computation cost of multiagent problems can be greatly reduced using an agent-by-agent PI approach
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Credit: IEEE/CAA Journal of Automatica Sinica
Computer scientists often encounter problems relevant to real-life scenarios. For instance, multiagent problems, a category characterized by multi-stage decision-making by multiple decision makers or agents, has relevant applications in search-and-rescue missions, firefighting, and emergency response.
Multiagent problems are often solved using a machine learning technique known as reinforcement learning (RL), which concerns itself with how intelligent agents make decisions in an environment unfamiliar to them. An approach usually adopted in such an endeavor is policy iteration (PI), which starts off with a base policy and then improves on it to generate a rollout policy (with the process of generation called a rollout ). Rollout is simple, reliable, and well-suited for an ....

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