基本信息
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职业迁徙
个人简介
My research explores principled solution methods for systems of agents (e.g., robots, network nodes, sensors, people) with uncertainty and limited communication. Many real-world scenarios have some communication cost, latency or noise (e.g., disaster response, networking, coordination over large distances). Due to these communication limitations, agents that can make decisions on their own are critical. My research seeks to develop fundamental theory as well as scalable algorithms that provide this high-quality autonomy with applications such as multi-robot navigation, search and rescue and surveillance problems.
Some keywords: Partially observable reinforcement learning, multi-agent reinforcement learning, multi-robot systems
Some keywords: Partially observable reinforcement learning, multi-agent reinforcement learning, multi-robot systems
研究兴趣
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Conference on Robot Learningpp.3309-3320, (2023)
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IEEE Access (2023): 47646-47658
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CoRR (2023)
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2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (2023): 9480-9487
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