Solution to reinforcement learning problems with artificial potential field

Article Properties
Cite
Xie, Li-juan, et al. “Solution to Reinforcement Learning Problems With Artificial Potential Field”. Journal of Central South University of Technology, vol. 15, no. 4, 2008, pp. 552-7, https://doi.org/10.1007/s11771-008-0104-x.
Xie, L.- juan, Xie, G.- rong, Chen, H.- wen, & Li, X.- li. (2008). Solution to reinforcement learning problems with artificial potential field. Journal of Central South University of Technology, 15(4), 552-557. https://doi.org/10.1007/s11771-008-0104-x
Xie L juan, Xie G rong, Chen H wen, Li X li. Solution to reinforcement learning problems with artificial potential field. Journal of Central South University of Technology. 2008;15(4):552-7.
Refrences
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  • Technology: Engineering (General). Civil engineering (General)
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Citations
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Efficient state representation with artificial potential fields for reinforcement learning

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Citations Analysis
The category Technology: Mechanical engineering and machinery 6 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Vision-based behavior prediction of ball carrier in basketball matches and was published in 2012. The most recent citation comes from a 2023 study titled Efficient state representation with artificial potential fields for reinforcement learning. This article reached its peak citation in 2022, with 2 citations. It has been cited in 10 different journals, 20% of which are open access. Among related journals, the Journal of Central South University cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year