| 来源类型 | Conference or Workshop Item (UNSPECIFIED) |
| 规范类型 | 其他 |
| Evolved neurocontrollers for pole balancing. | |
| Pasemann F; Dieckmann U | |
| 发表日期 | 1997 |
| 出处 | Biological and Artificial Computation: From Neuroscience to Technology - Proceedings of IWANN '97, 4-6 June 1997 |
| 出版年 | 1997 |
| 语种 | 英语 |
| 摘要 | An evolutionary algorithm for the development of neural networks with arbitrary connectivity is presented. The algorithm is not based on genetic Mgorithms, but is inspired by a biological theory of coevolving species. It sets no constraints on the number of neurons and the architecture of a network, and develops network topology and parameters like weights and bias terms simultaneously. Designed for generating neuromodules acting in embedded systems like autonomous agents, it can be used also for the evolution of neural networks solving nonlinear control problems. Here we report on a first test, where the algorithm is applied to a standard control problem: The balancing of an inverted pendulum. |
| 主题 | Adaptive Dynamics Network (ADN) |
| 关键词 | Algorithms Autonomous agents Bioinformatics Biology Electric network topology Control problems Inverted pendulum Network topology Neuro controllers Nonlinear control problems |
| URL | http://pure.iiasa.ac.at/id/eprint/5205/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/131926 |
| 推荐引用方式 GB/T 7714 | Pasemann F,Dieckmann U. Evolved neurocontrollers for pole balancing.. 1997. |
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