Name
Title | ||
|---|---|---|
An Overview and Practical Application of Biological Intelligence Algorithm Used in Intelligence Control |
Abstract | ||
|---|---|---|
Because of the disadvantages of the classical control methods, such as its fixed parameters, so the control effect of the classical control methods is greatly limited, and the Biological Intelligence Algorithm has provided a new way to break the bottleneck of classical control methods because of its adaptive and learning mechanism. With the improvement of the theory of reinforcement learning and deep learning, these theories have greatly improved the performance of the Biological Intelligence Algorithm. This paper summarizes seven kinds of intelligent algorithms which is used in intelligence control commonly, and emphatically analyzes the application examples of the combination of classical automatic control method and intelligent algorithms, especially reinforcement learning. The development status and future development trend of intelligent control based on reinforcement learning, deep learning and Brain-inspired Intelligence Technology in recent years are discussed for the first time in this paper. The purpose of this paper is to emphasize a new idea of combining intelligent algorithm with classical control method, and provide new ideas and practical examples for the research of intelligent control.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3297156.3297175 | Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence |
Keywords | DocType | ISBN |
Automatic control, Biological intelligence, Brain-inspired Intelligence, Intelligent control, Reinforcement learning | Conference | 978-1-4503-6606-9 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jie Chen | 1 | 91 | 38.15 |
| Sheng Cheng | 2 | 0 | 0.34 |
| Meng Xu | 3 | 211 | 18.89 |