Review Article
The Applicability of Reinforcement Learning Methods in the Development of Industry 4.0 Applications
Table 4
-test table of industrial field classes by RL method types.
| | Principle captured | Markov decision process | Multiarmed bandit | Dynamic | Temporal difference | Value function approximation | Policy gradient | Multiagent | Edge computing |
| | Energy, solar, power, electric | 0.52 | 1.7 | −12.77 | 21.87 | 0.94 | −11.54 | 2.05 | −2.77 | | Communication, networking, internet, 5G, Wi-Fi, mobile | −8.61 | −3.51 | 6.29 | −18.79 | 2.23 | 13.24 | −3.14 | 12.29 | | Wireless, radio, antenna, signal | 5.77 | 3.07 | −1.73 | −6.62 | 1.33 | −1.76 | 2.68 | −2.73 | | Vehicle, unmanned aerial vehicle, drone, aircraft | 8.44 | −1.39 | −2.32 | −2.89 | −2.49 | 5.9 | −6.94 | 1.68 | | Cyber-physical system, robot | −1.75 | 0 | 8.14 | 3.86 | −2.23 | −2.14 | 1.97 | −7.86 | | Manufacturing, factory | −3.33 | −0.55 | 4.16 | 1.36 | 1.23 | −2.54 | 1.52 | −1.84 | | City, building | −1.05 | 0.69 | −1.77 | 1.21 | −1.01 | −1.17 | 1.87 | 1.23 |
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