scholarly journals A storage expansion planning framework using reinforcement learning and simulation-based optimization

2021 ◽  
Vol 290 ◽  
pp. 116778
Author(s):  
Stamatis Tsianikas ◽  
Nooshin Yousefi ◽  
Jian Zhou ◽  
Mark D. Rodgers ◽  
David Coit
2021 ◽  
pp. 405-413
Author(s):  
Günther Schuh ◽  
Andreas Gützlaff ◽  
Matthias Schmidhuber ◽  
Jan Maetschke ◽  
Max Barkhausen ◽  
...  

2017 ◽  
Vol 133 ◽  
pp. 235-248 ◽  
Author(s):  
Ammar Jalalimanesh ◽  
Hamidreza Shahabi Haghighi ◽  
Abbas Ahmadi ◽  
Madjid Soltani

Author(s):  
Zhiwei (Tony) Qin ◽  
Xiaocheng Tang ◽  
Yan Jiao ◽  
Fan Zhang ◽  
Chenxi Wang ◽  
...  

In this demo, we will present a simulation-based human-computer interaction of deep reinforcement learning in action on order dispatching and driver repositioning for ride-sharing.  Specifically, we will demonstrate through several specially designed domains how we use deep reinforcement learning to train agents (drivers) to have longer optimization horizon and to cooperate to achieve higher objective values collectively. 


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