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@@ -26,7 +26,7 @@ TensorNEAT is a JAX-based libaray for NeuroEvolution of Augmenting Topologies (N
- JAX-based network for neuroevolution: - JAX-based network for neuroevolution:
- **Batch inference** across networks with different architectures, GPU-accelerated. - **Batch inference** across networks with different architectures, GPU-accelerated.
- Evolve networks with **irregular structures** and **fully customize** their behavior. - Evolve networks with **irregular structures** and **fully customize** their behavior.
- Visualize the network and represent it in **mathematical formulas** or codes. - Visualize the network and represent it in **mathematical formulas** or **codes**.
- GPU-accelerated NEAT implementation: - GPU-accelerated NEAT implementation:
- Run NEAT and HyperNEAT on GPUs. - Run NEAT and HyperNEAT on GPUs.
@@ -78,15 +78,15 @@ pipeline.show(state, best)
Obtain result in a few generations: Obtain result in a few generations:
``` ```
Fitness limit reached! Fitness limit reached!
input: [0. 0. 0.], target: [0.], predict: [0.00066471] input: [0. 0. 0.], target: [0.], predict: [0.00037953]
input: [0. 0. 1.], target: [1.], predict: [0.9992988] input: [0. 0. 1.], target: [1.], predict: [0.9990619]
input: [0. 1. 0.], target: [1.], predict: [0.9988666] input: [0. 1. 0.], target: [1.], predict: [0.9991497]
input: [0. 1. 1.], target: [0.], predict: [0.00107922] input: [0. 1. 1.], target: [0.], predict: [0.0004661]
input: [1. 0. 0.], target: [1.], predict: [0.9987184] input: [1. 0. 0.], target: [1.], predict: [0.998262]
input: [1. 0. 1.], target: [0.], predict: [0.00093677] input: [1. 0. 1.], target: [0.], predict: [0.00077246]
input: [1. 1. 0.], target: [0.], predict: [0.00060118] input: [1. 1. 0.], target: [0.], predict: [0.00082464]
input: [1. 1. 1.], target: [1.], predict: [0.99927646] input: [1. 1. 1.], target: [1.], predict: [0.99909043]
loss: 8.484730074087565e-07 loss: 8.861396736392635e-07
``` ```
4. **Visualize the best network**: 4. **Visualize the best network**:
```python ```python