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Continual Reasoning: Non-Monotonic Reasoning in Neurosymbolic AI using Continual Learning
In this paper, we show that by combining a neural-symbolic system with methods from continual learning, LTN can obtain a higher level of accuracy when addressing non-monotonic reasoning tasks.
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