Reinforcement learning for rule selection in end to end differentiable proving
Neural Theorem Provers (NTPs) are neuro-symbolic models that combine deep learning with a system of logic. They can learn representations for data, induce rules, are naturally interpretable, come with built-in explanations for conclusions, and demonstrate the capacity for systematic generalization....
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| Định dạng: | Luận văn |
| Ngôn ngữ: | English |
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2021
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