Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Koh, Joewie J."'
Publikováno v:
Proceedings of the 2024 American Control Conference (ACC), 2024
Effective multi-agent collaboration is imperative for solving complex, distributed problems. In this context, two key challenges must be addressed: first, autonomously identifying optimal objectives for collective outcomes; second, aligning these obj
Externí odkaz:
http://arxiv.org/abs/2404.03984
Publikováno v:
Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020, pp. 7985-7992
Multi-robot cooperation requires agents to make decisions that are consistent with the shared goal without disregarding action-specific preferences that might arise from asymmetry in capabilities and individual objectives. To accomplish this goal, we
Externí odkaz:
http://arxiv.org/abs/2008.00679
Autor:
Ding, Guohui, Koh, Joewie J., Merckaert, Kelly, Vanderborght, Bram, Nicotra, Marco M., Heckman, Christoffer, Roncone, Alessandro, Chen, Lijun
Publikováno v:
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2020, pp. 1831-1833
We consider solving a cooperative multi-robot object manipulation task using reinforcement learning (RL). We propose two distributed multi-agent RL approaches: distributed approximate RL (DA-RL), where each agent applies Q-learning with individual re
Externí odkaz:
http://arxiv.org/abs/2003.09540
Autor:
Koh, Joewie J., Rhodes, Barton
Publikováno v:
Proceedings of the 2018 IEEE International Conference on Big Data, 2018, pp. 2966-2971
Domain generation algorithms (DGAs) are frequently employed by malware to generate domains used for connecting to command-and-control (C2) servers. Recent work in DGA detection leveraged deep learning architectures like convolutional neural networks
Externí odkaz:
http://arxiv.org/abs/1811.08705