A spatially explicit reinforcement learning model for geographic knowledge graph summarization

2019 ◽  
Vol 23 (3) ◽  
pp. 620-640 ◽  
Author(s):  
Bo Yan ◽  
Krzysztof Janowicz ◽  
Gengchen Mai ◽  
Rui Zhu
Keyword(s):  
Reinforcement Learning ◽  
Learning Model ◽  
Knowledge Graph ◽  
Spatially Explicit ◽  
Geographic Knowledge ◽  
Graph Summarization ◽  
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.

Sign in / Sign up

Export Citation Format

Share Document