Fetching the paper…
Reading the bibliography…
We propose and design recommendation systems that incentivize efficient exploration.
Introduction to multi-armed bandits
Aleksandrs Slivkins · 1904
Earlier work this paper cites.
Reaching a Consensus
Morris H. DeGroot · 1974
Earlier work this paper cites.
The informational role of warranties and private disclosure about product quality
Sanford J Grossman · 1981
Earlier work this paper cites.
Good news and bad news: Representation theorems and applications
Paul R Milgrom · 1981
Earlier work this paper cites.
Asymptotically efficient Adaptive Allocation Rules
Tze Leung Lai and Herbert Robbins · 1985
Earlier work this paper cites.
Relying on the information of interested parties
Paul Milgrom and John Roberts · 1986
Earlier work this paper cites.
A simple model of herd behavior
Abhijit V. Banerjee · 1992
Earlier work this paper cites.
A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades
Sushil Bikhchandani, David Hirshleifer, and Ivo Welch · 1992
Earlier work this paper cites.
Sequential sales, learning, and cascades
Ivo Welch · 1992
Earlier work this paper cites.
The nonstochastic multiarmed bandit problem
Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, and Robert E. Schapire · 1995
Earlier work this paper cites.
Case-Based Decision Theory
Itzhak Gilboa and David Schmeidler · 1995
Earlier work this paper cites.
Strategic Experimentation
Patrick Bolton and Christopher Harris · 1999
Earlier work this paper cites.
Pathological outcomes of observational learning
Lones Smith and Peter Sørensen · 2000
Earlier work this paper cites.
Strategic Experimentation with Exponential Bandits
Godfrey Keller, Sven Rady, and Martin Cripps · 2005
Earlier work this paper cites.
Bandit Problems
Dirk Bergemann and Juuso Välimäki · 2006
Earlier work this paper cites.
The network structure of exploration and exploitation
David Lazer and Allan Friedman · 2007
Earlier work this paper cites.
Characterizing truthful multi-armed bandit mechanisms
Moshe Babaioff, Yogeshwer Sharma, and Aleksandrs Slivkins · 2009
Earlier work this paper cites.
Naive learning in social networks and the wisdom of crowds
Benjamin Golub and Matthew O Jackson · 2010
Earlier work this paper cites.
Bayesian learning in social networks
Daron Acemoglu, Munther A Dahleh, Ilan Lobel, and Asuman Ozdaglar · 2011
Earlier work this paper cites.
Multi-Armed Bandit Allocation Indices
John Gittins, Kevin Glazebrook, and Richard Weber · 2011
Cited alongside, same era.
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
Sébastien Bubeck and Nicolo Cesa-Bianchi · 2012
Cited alongside, same era.
Recommender systems as mechanisms for social learning
Yeon-Koo Che and Johannes Hörner · 2013
Cited alongside, same era.
Implementing the “wisdom of the crowd”
Ilan Kremer, Yishay Mansour, and Motty Perry · 2013
Cited alongside, same era.
Incentivizing exploration
Peter Frazier, David Kempe, Jon M. Kleinberg, and Robert Kleinberg · 2014
Cited alongside, same era.
Information diffusion in networks through social learning
Ilan Lobel and Evan Sadler · 2015
Cited alongside, same era.
Ratings design and barriers to entry
Nikhil Vellodi · 2018
Closest in time.
Social learning and the innkeeper’s challenge
Gal Bahar, Rann Smorodinsky, and Moshe Tennenholtz · 2019
Closest in time.
Batched multi-armed bandits problem
Zijun Gao, Yanjun Han, Zhimei Ren, and Zhengqing Zhou · 2019
Closest in time.
Bayesian exploration with heterogenous agents
Nicole Immorlica, Jieming Mao, Aleksandrs Slivkins, and Steven Wu · 2019
Closest in time.
Games of incomplete information played by statisticians
Annie Liang · 2019
Closest in time.
Testing models of social learning on networks: Evidence from two experiments
Arun G Chandrasekhar, Horacio Larreguy, and Juan Pablo Xandri · 2020
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Bayesian incentive-compatible bandit exploration
Yishay Mansour, Aleksandrs Slivkins, and Vasilis Syrgkanis · 2015
Cited alongside, same era.
Economic recommendation systems
Gal Bahar, Rann Smorodinsky, and Moshe Tennenholtz · 2016
Cited alongside, same era.
Learning in social networks
Benjamin Golub and Evan D. Sadler · 2016
Cited alongside, same era.
Bayesian exploration: Incentivizing exploration in Bayesian games
Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis, and Steven Wu · 2016
Cited alongside, same era.
Batched bandit problems
Vianney Perchet, Philippe Rigollet, Sylvain Chassang, and Erik Snowberg · 2016
Cited alongside, same era.
Learning From Reviews: The Selection Effect and the Speed of Learning
Daron Acemoglu, Ali Makhdoumi, Azarakhsh Malekian, and Asuman Ozdaglar · 2017
Cited alongside, same era.
Machine learning for strategic inference
In-Koo Cho and Jonathan Libgober · 2020
Closest in time.
Aggregative efficiency of bayesian learning in networks
Krishna Dasaratha and Kevin He · 2020
Closest in time.
Bandit Algorithms
Tor Lattimore and Csaba Szepesvári · 2020
Closest in time.
Statistical inference in games
Yuval Salant and Josh Cherry · 2020
Closest in time.
Inference for batched bandits
Kelly Zhang, Lucas Janson, and Susan Murphy · 2020
Closest in time.
An experiment on network density and sequential learning
Krishna Dasaratha and Kevin He · 2021
Closest in time.
Regret bounds for batched bandits
Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, and Vahab S. Mirrokni · 2021
Closest in time.
The price of incentivizing exploration: A characterization via thompson sampling and sample complexity
Mark Sellke and Aleksandrs Slivkins · 2021
Closest in time.
Incentivizing combinatorial bandit exploration
Xinyan Hu, Dung Daniel T. Ngo, Aleksandrs Slivkins, and Zhiwei Steven Wu · 2022
Closest in time.
Bandit social learning under myopic behavior
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin, and Aleksandrs Slivkins · 2023
Closest in time.
Aleksandrs Slivkins · 2023
Closest in time.
Incentives and exploration in reinforcement learning
Max Simchowitz and Aleksandrs Slivkins · 2024
Closest in time.