Exploration Via Randomization
Exploration Via Randomization is a stochastic decision-making strategy within the exploration-exploitation tradeoff framework that distinguishes itself by introducing controlled randomness into action selection to systematically sample uncertain options and gather information about the environment.
8
Publications
690
Citations
14
Authors
9
Institutions
Publications per year
2017–2026
5
8
Deep Exploration via Randomized Value Functions
Ian Osband, Benjamin Van Roy, Daniel Russo et al. · Journal of Machine Learning Research · 2019 · 119 citations
Deep Exploration via Randomized Value Functions
Ian Osband, Benjamin Van Roy, Daniel Russo et al. · arXiv (Cornell University) · 2017 · 68 citations · Full text
1–5 of 8
14
3
h-index
3
h-index
3
h-index
3
h-index
Rutgers, The State University of New Jersey, United States
2 publications · 253 citations
2
h-index
1–5 of 14
9
Université de Montréal
Montreal, Canada
2 h-index
2 publications
253 citations
University of Arizona
Tucson, United States
2 h-index
2 publications
253 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
2 h-index
2 publications
253 citations
Oregon Health & Science University
Portland, United States
2 h-index
2 publications
253 citations
I-Shou University
Kaohsiung City, Taiwan
1 h-index
4 publications
420 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
1 publications
46 citations
Stanford University
Stanford, United States
1 h-index
3 publications
249 citations
University Hospital, Newark
Newark, United States
1 h-index
1 publications
234 citations
1–8 of 9
Repository · 3 publications · 167 citations
3
h-index
JMLR · 1 publications · 119 citations
1
h-index
IJRR · 1 publications · 46 citations
1
h-index
1 publications · 234 citations
1
h-index
1–4