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of 24
pro vyhledávání: '"Kailas, Siva"'
Informative path planning (IPP) is an important planning paradigm for various real-world robotic applications such as environment monitoring. IPP involves planning a path that can learn an accurate belief of the quantity of interest, while adhering t
Externí odkaz:
http://arxiv.org/abs/2410.17186
Autor:
Gadipudi, Srikar Babu, Deolasee, Srujan, Kailas, Siva, Luo, Wenhao, Sycara, Katia, Kim, Woojun
Informative path planning (IPP) is a crucial task in robotics, where agents must design paths to gather valuable information about a target environment while adhering to resource constraints. Reinforcement learning (RL) has been shown to be effective
Externí odkaz:
http://arxiv.org/abs/2409.16830
Autor:
Drolet, Michael, Stepputtis, Simon, Kailas, Siva, Jain, Ajinkya, Peters, Jan, Schaal, Stefan, Amor, Heni Ben
Amidst the wide popularity of imitation learning algorithms in robotics, their properties regarding hyperparameter sensitivity, ease of training, data efficiency, and performance have not been well-studied in high-precision industry-inspired environm
Externí odkaz:
http://arxiv.org/abs/2408.06536
Autor:
Jong, Andrew, Yu, Mukai, Dhrafani, Devansh, Kailas, Siva, Moon, Brady, Sycara, Katia, Scherer, Sebastian
We present the Wildland-fire Infrared Thermal (WIT-UAS) dataset for long-wave infrared sensing of crew and vehicle assets amidst prescribed wildland fire environments. While such a dataset is crucial for safety monitoring in wildland fire application
Externí odkaz:
http://arxiv.org/abs/2312.09159
Explicit communication among humans is key to coordinating and learning. Social learning, which uses cues from experts, can greatly benefit from the usage of explicit communication to align heterogeneous policies, reduce sample complexity, and solve
Externí odkaz:
http://arxiv.org/abs/2302.14276
Communication enables agents to cooperate to achieve their goals. Learning when to communicate, i.e., sparse (in time) communication, and whom to message is particularly important when bandwidth is limited. Recent work in learning sparse individualiz
Externí odkaz:
http://arxiv.org/abs/2212.00115
Learning interpretable communication is essential for multi-agent and human-agent teams (HATs). In multi-agent reinforcement learning for partially-observable environments, agents may convey information to others via learned communication, allowing t
Externí odkaz:
http://arxiv.org/abs/2201.07452
In this paper we consider infinite horizon discounted dynamic programming problems with finite state and control spaces, partial state observations, and a multiagent structure. We discuss and compare algorithms that simultaneously or sequentially opt
Externí odkaz:
http://arxiv.org/abs/2011.04222
Autor:
Capiola, August, Lyons, Joseph B., Harris, Krista N., Hamdan, Izz aldin, Kailas, Siva, Sycara, Katia
Publikováno v:
In Computers in Human Behavior December 2023 149
Akademický článek
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