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| Title | Genetic Programming Learning and the Cobweb Model |
| Creator | Chen, Shu-heng;Yeh, Chia-Hsuan 陳樹衡 |
| Contributor | 經濟系 |
| Date | 1996 |
| Date Issued | 11-May-2015 14:50:36 (UTC+8) |
| Summary | Using genetic programming to model the cobweb model as a multiagent system, this chapter generalizes the work done by Arifovic (1994), which is based on genetic algorithms. We find that the rational expectations equilibrium price which can be discovered by ge- netic algorithms can also be discovered by genetic programming. Furthermore, genetic programming requires much less prior knowledge than genetic algorithms. The reasonable upper limit of the price and the characteristic of the equilibrium which is assumed as the prior knowledge in genetic algorithms can all be discovered by genetic programming. In addition, GP-based markets have a self-stabilizing force which is capable of bringing any deviations caused by mutation back to the rational expectations equilibrium price. All of these features show that genetic programming can be a very useful tool for economists to model learning and adaptation in multiagent systems. In particular, with respect to the understanding of the dynamics of the market process, it provides us with a visible foundation for the "invisible hand". |
| Relation | Advances in Genetic Programming 2, in P. Angeline and K. E. Kinnear, Jr.(eds.), Chapter 22, Cambridge |
| Type | conference |
| dc.contributor | 經濟系 | |
| dc.creator (作者) | Chen, Shu-heng;Yeh, Chia-Hsuan | |
| dc.creator (作者) | 陳樹衡 | zh_TW |
| dc.date (日期) | 1996 | |
| dc.date.accessioned | 11-May-2015 14:50:36 (UTC+8) | - |
| dc.date.available | 11-May-2015 14:50:36 (UTC+8) | - |
| dc.date.issued (上傳時間) | 11-May-2015 14:50:36 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/75074 | - |
| dc.description.abstract (摘要) | Using genetic programming to model the cobweb model as a multiagent system, this chapter generalizes the work done by Arifovic (1994), which is based on genetic algorithms. We find that the rational expectations equilibrium price which can be discovered by ge- netic algorithms can also be discovered by genetic programming. Furthermore, genetic programming requires much less prior knowledge than genetic algorithms. The reasonable upper limit of the price and the characteristic of the equilibrium which is assumed as the prior knowledge in genetic algorithms can all be discovered by genetic programming. In addition, GP-based markets have a self-stabilizing force which is capable of bringing any deviations caused by mutation back to the rational expectations equilibrium price. All of these features show that genetic programming can be a very useful tool for economists to model learning and adaptation in multiagent systems. In particular, with respect to the understanding of the dynamics of the market process, it provides us with a visible foundation for the "invisible hand". | |
| dc.format.extent | 160427 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Advances in Genetic Programming 2, in P. Angeline and K. E. Kinnear, Jr.(eds.), Chapter 22, Cambridge | |
| dc.title (題名) | Genetic Programming Learning and the Cobweb Model | |
| dc.type (資料類型) | conference | en |