scholarly journals A Reinforcement Learning Model Based on Temporal Difference Algorithm

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 121922-121930 ◽  
Author(s):  
Xiali Li ◽  
Zhengyu Lv ◽  
Song Wang ◽  
Zhi Wei ◽  
Licheng Wu
Keyword(s):  
Reinforcement Learning ◽  
Learning Model ◽  
Temporal Difference ◽  
Model Based ◽  
Reinforcement Learning Model

scholarly journals Modeling individual variation in visual search with reinforcement learning

2020 ◽  
Author(s):  
Ben Lonnqvist ◽  
Micha Elsner ◽  
Amelia R. Hunt ◽  
Alasdair D F Clarke
Keyword(s):  
Visual Acuity ◽  
Reinforcement Learning ◽  
Visual Search ◽  
Individual Variation ◽  
Learning Model ◽  
Participant Preferences ◽  
Search Experiment ◽  
Reinforcement Learning Model ◽  
Specific Learning

Experiments on the efficiency of human search sometimes reveal large differences between individual participants. We argue that reward-driven task-specific learning may account for some of this variation. In a computational reinforcement learning model of this process, a wide variety of strategies emerge, despite all simulated participants having the same visual acuity. We conduct a visual search experiment, and replicate previous findings that participant preferences about where to search are highly varied, with a distribution comparable to the simulated results. Thus, task-specific learning is an under-explored mechanism by which large inter-participant differences can arise.

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