2017
IJCAI
IJCAI 2017
Robotic Strategic Behavior in Adversarial Environments
Abstract
The presence of robots in areas containing threats is becoming more prevalent, due to their ability to perform missions accurately, efficiently, and with little risk to humans. Having the robots handle adversarial forces in missions such as search and rescue, intelligence gathering, border protection and humanitarian assistance, raises many new, exciting research challenges. This paper describes recent research achievements in areas related to robotic mission planning in adversarial environments, including multi-robot patrolling, robotic coverage, multi-robot formation, and navigation, and suggests possible future research directions.
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Interdisciplinary Bridge
— Artificial Intelligence and Reinforcement Learning
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Keyword Pioneer
— adversarial environment
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio