Multi-agent framework for third party logistics in E-commerce
By Wang Ying, Dayong Sang. 2005
137 citations recorded by the source corpus.
Subfields: Industrial and Manufacturing Engineering, Management Information Systems, Management of Technology and Innovation
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In Industrial and Manufacturing Engineering
In Management Information Systems
Citations in the corpus
- Counterfactual Multi-Agent Policy Gradients (2017, background): “Many complex reinforcement learning (RL) problems such as the coordination of autonomous vehicles (Cao et al., 2013), network packet delivery (Ye et al., 2015), and distributed logistics (Ying & Dayong, 2005) are naturally modelled as cooperative multi-agent systems.”
- Q-value Path Decomposition for Deep Multiagent Reinforcement Learning (2020, background): “Cooperative multiagent systems (MAS) have been shown to be a useful paradigm in numerous applications, e.g., the coordination of autonomous vehicles (Cao et al., 2012) and optimizing the productivity of a factory in distributed logistics (Ying & Sang, 2005).”
- Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning (2020, background): “Complex tasks such as the coordination of autonomous vehicles (Cao et al., 2012), optimizing the productivity of a factory in distributed logistics (Ying & Sang, 2005) and energy distribution, often modeled as cooperative multi-agent learning problems, have great 1 Tianjin Univeristy, China 2…”
- Multi-Agent Actor-Critic with Hierarchical Graph Attention Network (2019, unknown): “…agents are also important modeling paradigms in various engineering systems, such as smart grids (Dall’Anese, Zhu, and Giannakis 2013), logistics (Ying and Dayong 2005; Cao et al. 2013), and distributed vehicles/robots (Corke, Peterson, and Rus 2005; Fax and Murray 2004; Matignon et al. 2012).”