However, exactly how cognitive adequacy is ensured has been often left implicit, and connections with cognitive science and psychology have only recently been taken up. This cognitive adequacy has important ramifications for the explainability of approaches in knowledge representation, which on its turn is essential for the trustworthiness of these approaches. sub-symbolic approaches, such as machine learning. It is often claimed that this declarative nature makes knowledge representation cognitively more adequate than e.g. Knowledge representation is a lively and well-established field of AI, where knowledge and belief is represented declaratively and suitable for machine processing.
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