Controlling chaos by GA-based reinforcement learning neural network
โ Scribed by Chin-Teng Lin, ; Chong-Ping Jou,
- Book ID
- 125517129
- Publisher
- IEEE
- Year
- 1999
- Tongue
- English
- Weight
- 174 KB
- Volume
- 10
- Category
- Article
- ISSN
- 1045-9227
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Figure 1 Performance of the spiking neural network. A. The free-energies estimated by both the spiking neural network and the original RBM. They are highly correlated (correlation coefficient, r = 0.9485) B. The hidden neurons activation on the two principal components. The hidden activation pattern
RAM-based neural networks are designed to be efficiently implemented in hardware. The desire to retain this property influences the training algorithms used, and has led to the use of reinforcement (reward-penalty) learning. An analysis of the reinforcement algorithm applied to RAM-based nodes has s