基于汤普森采样的机器人团队多目标搜索

2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI:10.1109/ICDSCA56264.2022.9988679

Yidan Chen, Melvin Ticiano Gao

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引用次数: 0

摘要

基于探索与开发权衡的多臂盗匪问题的不同解与算法，包括汤普森采样。事实证明，与流行的解决方法相比，该方法具有竞争力。将MAB问题转化为多机器人搜索问题。展示了用动态汤普森采样方法求解多机器人搜索问题的数据。

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Multi-target Search Using Teams of Robots Based on Thompson Sampling

Different Solutions and algorithm to the Multi-Armed Bandit (MAB) problem using method of exploration and exploitation trade-off, including Thompson Sampling. Which proved to have competitive results compared to popular methods of solution. Formulated MAB problem into Multi-robot Search problem. Showed data solving multi-robot search problem with Dynamic Thompson sampling.

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2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)

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