Abstract
In this paper, a novel self-generating neuro-fuzzy system through reinforcements is proposed. Not only the weights of the network but also the architecture of the whole network are all learned through reinforcement learning. The proposed neuro-fuzzy system is applied to the inverted pendulum system to demonstrate its performance.
| Original language | English |
|---|---|
| Title of host publication | Recent Advances in Computers, Computing and Communications |
| Publisher | World Scientific and Engineering Academy and Society |
| Pages | 332-337 |
| Number of pages | 6 |
| ISBN (Print) | 9608052629 |
| State | Published - 2002 |
Keywords
- Neural network
- Neuro-fuzzy system
- Reinforcement learning