Reinforcement learning based on human-computer interaction

Author(s):  
Fang Liu ◽  
Jian-Bo Su
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. 


2005 ◽  
Author(s):  
John Neumann ◽  
Jennifer M. Ross ◽  
Peter Terrence ◽  
Mustapha Mouloua

Author(s):  
Himanshu Bansal ◽  
Rizwan Khan

The advancement in the development of computer technology has led to the idea of human computer interaction. Research experiments in human computer interaction involves the young age group of people that are educated and technically knowledgeable. This paper focuses on the mental model in Human Computer Interaction. There are various approaches of this review paper and one of them is highlighting current approach, results and the trends in the human computer interaction and the second approach is to find out the research that have been invented a long time before and are currently lagging behind. This paper also focuses on the emotional intelligence of a user to become more user like, fidelity prototyping. The development and design of an automated system that perform such task is still being accomplished.


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