2019
EMNLP
EMNLP 2019
Commonsense inference in human-robot communication
Abstract
AbstractNatural language communication between machines and humans are still constrained. The article addresses a gap in natural language understanding about actions, specifically that of understanding commands. We propose a new method for commonsense inference (grounding) of high-level natural language commands into specific action commands for further execution by a robotic system. The method allows to build a knowledge base that consists of a large set of commonsense inferences. The preliminary results have been presented.
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Interdisciplinary Bridge
— Artificial Intelligence and Knowledge & Reasoning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Agent Systems
Artificial Intelligence > Core AI > Human-AI Interaction
Natural Language Processing > Applications > Intent Classification
Knowledge & Reasoning > Representation > Knowledge Representation
Knowledge & Reasoning > Reasoning > Causal Inference
Artificial Intelligence > Core AI > Robotics
Artificial Intelligence > Core AI > Natural Language Processing
Artificial Intelligence > Core AI > Knowledge