Deep Reinforcement Learning of Abstract Reasoning from Demonstrations

Extracting a set of generalizable rules that govern the dynamics of complex, high-level interactions between humans based only on observations is a high-level cognitive ability. Mastery of this skill marks a significant milestone in the human developmental process. A key challenge in designing such...

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Vydáno v:	2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI) s. 160 - 168
Hlavní autoři:	Clark-Turner, Madison, Begum, Momotaz
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	New York, NY, USA ACM 26.02.2018
Edice:	ACM Conferences
Témata:	Abstract Reasoning Analytical models Cognition Computing methodologies > Artificial intelligence > Computer vision > Computer vision tasks > Vision for robotics Computing methodologies > Artificial intelligence > Knowledge representation and reasoning Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Cognitive robotics Computing methodologies > Machine learning > Learning paradigms > Supervised learning Deep Learning Human-robot interaction Learning from Demonstration Object recognition Probabilistic logic Reinforcement learning Theory of computation > Logic > Abstraction Theory of computation > Logic > Automated reasoning Training deep learning abstract reasoning learning from demonstration
ISBN:	9781450349536, 1450349536
ISSN:	2167-2148
On-line přístup:	Získat plný text
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