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Detect, understand, act: A neuro-symbolic hierarchical reinforcement learning framework
In this paper we introduce Detect, Understand, Act (DUA), a neuro-symbolic reinforcement
learning framework. The Detect component is composed of a traditional computer vision …
learning framework. The Detect component is composed of a traditional computer vision …
pix2rule: End-to-end Neuro-symbolic Rule Learning
Humans have the ability to seamlessly combine low-level visual input with high-level
symbolic reasoning often in the form of recognising objects, learning relations between them …
symbolic reasoning often in the form of recognising objects, learning relations between them …
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework
In this paper we introduce Detect, Understand, Act (DUA), a neuro-symbolic reinforcement
learning framework. The Detect component is composed of a traditional computer vision …
learning framework. The Detect component is composed of a traditional computer vision …
[PDF][PDF] Automatic Concept Extraction and Its Use in Explaining Video Classification
For most tasks, fully neural architectures are undisputedly the best performing and most
widely used models in machine learning. However, they are mostly uninterpretable, making …
widely used models in machine learning. However, they are mostly uninterpretable, making …