1. Reinforcement learning for DSS based on multi-agent model: A case of lake water environment DSS.
- Author
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NI Jian-ju, LIU Ming-hua, REN Li, and ZHANG Chuan-biao
- Subjects
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REINFORCEMENT learning , *WATER pollution control industry , *DECISION support systems , *WATER pollution , *AQUATIC organisms - Abstract
The lake water environmental problem has been more and more serious. It is a very important subject to find a more effective way of water pollution control. In this paper, the lake water environment decision support system (DSS) is set up, using the knowledge and methods of complex system and multi-agent modeling. The various entities in the lake water environment (such as government, polluting enterprise and a lot of aquatic organisms) are abstracted as the agents, which have some certain intelligence. A method based on reinforcement learning is proposed to achieve the intelligent prediction and warning of the lake water pollution. At last, a preliminary simulation experiment is conducted on the application of Taihu Lake basin. The experiment results show that the proposed method is effective. [ABSTRACT FROM AUTHOR]
- Published
- 2012