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Zheng Li, Xinkai Chen, Jiaqing Fu, Ning Xie and Tingting Zhao
With the development of electronic game technology, the content of electronic games presents a larger number of units, richer unit attributes, more complex game mechanisms, and more diverse team strategies. Multi-agent deep reinforcement learning shines ...
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Huiting Wang, Yazhi Liu, Wei Li and Zhigang Yang
In data center networks, when facing challenges such as traffic volatility, low resource utilization, and the difficulty of a single traffic scheduling strategy to meet demands, it is necessary to introduce intelligent traffic scheduling mechanisms to im...
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Yogeswaranathan Kalyani, Liam Vorster, Rebecca Whetton and Rem Collier
In the last decade, digital twin (DT) technology has received considerable attention across various domains, such as manufacturing, smart healthcare, and smart cities. The digital twin represents a digital representation of a physical entity, object, sys...
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Martin Kenyeres, Ivana Budinská, Ladislav Hluchý and Agostino Poggi
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Satoshi Warita and Katsuhide Fujita
Recently, multi-agent systems have become widespread as essential technologies for various practical problems. An essential problem in multi-agent systems is collaborative automating picking and delivery operations in warehouses. The warehouse commission...
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Yusheng Chen, Zhaofa Sun, Yanmei Wang, Ye Ma and Weili Yang
In the context of global food security and the pursuit of sustainable agricultural development, fostering synergistic innovation in the seed industry is of strategic importance. However, the collaborative innovation process between seed companies, resear...
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Shuo Liu, Bohan Feng, Youyi Bi and Dan Yu
Mobile robots play an important role in smart factories, though efficient task assignment and path planning for these robots still present challenges. In this paper, we propose an integrated task- and path-planning approach with precedence constrains in ...
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Xin Liao and Khoi D. Hoang
Distributed Constraint Optimization Problems (DCOPs) are an efficient framework widely used in multi-agent collaborative modeling. The traditional DCOP framework assumes that variables are discrete and constraint utilities are represented in tabular form...
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Siyao Lu, Rui Xu, Zhaoyu Li, Bang Wang and Zhijun Zhao
The International Lunar Research Station, to be established around 2030, will equip lunar rovers with robotic arms as constructors. Construction requires lunar soil and lunar rovers, for which rovers must go toward different waypoints without encounterin...
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Xiaoping Zhang, Yuanpeng Zheng, Li Wang, Arsen Abdulali and Fumiya Iida
Multi-agent collaborative target search is one of the main challenges in the multi-agent field, and deep reinforcement learning (DRL) is a good way to learn such a task. However, DRL always faces the problem of sparse reward, which to some extent reduces...
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