Fetching the paper…
Reading the bibliography…
We introduce the use of reinforcement learning for indirect mechanisms, working with the existing class of sequential price mechanisms, which generalizes both serial dictatorship and posted price mechanisms and essentially characterizes all strongly obviously strategyproof mechanisms.
A markovian decision process
Richard Bellman · 1957
Earlier work this paper cites.
Speech pattern discrimination and multilayer perceptrons
H Bourlard and CJ Wellekens · 1989
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Random serial dictatorship and the core from random endowments in house allocation problems
Atila Abdulkadiroğlu and Tayfun Sönmez · 1998
Earlier work this paper cites.
Planning and acting in partially observable stochastic domains
Leslie Pack Kaelbling, Michael L Littman, and Anthony R Cassandra · 1998
Earlier work this paper cites.
Complexity of mechanism design
Vincent Conitzer and Tuomas Sandholm · 2002
Earlier work this paper cites.
Co-evolutionary auction mechanism design: A preliminary report
Steve Phelps, Peter McBurney, Simon Parsons, and Elizabeth Sklar · 2002
Earlier work this paper cites.
Applying evolutionary game theory to auction mechanism design
Andrew Byde · 2003
Earlier work this paper cites.
Sequences of take-it-or-leave-it offers: Near-optimal auctions without full valuation revelation
Tuomas Sandholm and Andrew Gilpin · 2003
Earlier work this paper cites.
Preference elicitation and query learning
Avrim Blum, Jeffrey Jackson, Tuomas Sandholm, and Martin Zinkevich · 2004
Earlier work this paper cites.
Self-interested automated mechanism design and implications for optimal combinatorial auctions
Vincent Conitzer and Tuomas Sandholm · 2004
Earlier work this paper cites.
Variance reduction techniques for gradient estimates in reinforcement learning
Evan Greensmith, Peter L Bartlett, and Jonathan Baxter · 2004
Earlier work this paper cites.
Applying learning algorithms to preference elicitation
Sebastien M Lahaie and David C Parkes · 2004
Earlier work this paper cites.
Methods for empirical game-theoretic analysis
Michael P. Wellman · 2006
Earlier work this paper cites.
Evolutionary mechanism design: a review
Steve Phelps, Peter McBurney, and Simon Parsons · 2010
Earlier work this paper cites.
Learning on a budget: posted price mechanisms for online procurement
Ashwinkumar Badanidiyuru, Robert Kleinberg, and Yaron Singer · 2012
Earlier work this paper cites.
Optimal multi-dimensional mechanism design: Reducing revenue to welfare maximization
Yang Cai, Constantinos Daskalakis, and S Matthew Weinberg · 2012
Cited alongside, same era.
Matroid prophet inequalities
Robert Kleinberg and Seth Matthew Weinberg · 2012
Cited alongside, same era.
Understanding incentives: Mechanism design becomes algorithm design
Yang Cai, Constantinos Daskalakis, and S Matthew Weinberg · 2013
Cited alongside, same era.
Revenue optimization in the generalized second-price auction
David Robert Martin Thompson and Kevin Leyton-Brown · 2013
Cited alongside, same era.
The complexity of optimal multidimensional pricing
Xi Chen, Ilias Diakonikolas, Dimitris Paparas, Xiaorui Sun, and Mihalis Yannakakis · 2014
Cited alongside, same era.
The sample complexity of revenue maximization
Richard Cole and Tim Roughgarden · 2014
Cited alongside, same era.
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
Yuhuai Wu, Elman Mansimov, Roger B Grosse, Shun Liao, and Jimmy Ba · 2017
Later among the works it cites.
Designing core-selecting payment rules: A computational search approach
Benedikt Bünz, Benjamin Lubin, and Sven Seuken · 2018
Later among the works it cites.
Reinforcement mechanism design for e-commerce
Qingpeng Cai, Aris Filos-Ratsikas, Pingzhong Tang, and Yiwei Zhang · 2018
Later among the works it cites.
Deep learning for multi-facility location mechanism design
Noah Golowich, Harikrishna Narasimhan, and David C. Parkes · 2018
Later among the works it cites.
The sample complexity of up-to- ϵ \epsilon multi-dimensional revenue maximization
Yannai A. Gonczarowski and S. Matthew Weinberg · 2018
Later among the works it cites.
Empirical mechanism design: Designing mechanisms from data
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Payment rules through discriminant-based classifiers
Paul Dütting, Felix Fischer, Pichayut Jirapinyo, John K Lai, Benjamin Lubin, and David C Parkes · 2015
Cited alongside, same era.
Combinatorial auctions via posted prices
Michal Feldman, Nick Gravin, and Brendan Lucier · 2015
Cited alongside, same era.
Posted prices, smoothness, and combinatorial prophet inequalities
Paul Dütting, Michal Feldman, Thomas Kesselheim, and Brendan Lucier · 2016
Cited alongside, same era.
Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Automated mechanism design without money via machine learning
Harikrishna Narasimhan, Shivani Brinda Agarwal, and David C Parkes · 2016
Cited alongside, same era.
Obviously strategy-proof mechanisms
Shengwu Li · 2017
Cited alongside, same era.
Enrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, and Amy Greenwald · 2019
Later among the works it cites.
Fast iterative combinatorial auctions via bayesian learning
Gianluca Brero, Sébastien Lahaie, and Sven Seuken · 2019
Later among the works it cites.
Optimal auctions through deep learning
Paul Duetting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, and Sai Srivatsa Ravindranath · 2019
Later among the works it cites.
Serial dictatorship mechanisms with reservation prices
Bettina Klaus and Alexandru Nichifor · 2019
Later among the works it cites.
A theory of simplicity in games and mechanism design
Marek Pycia and Peter Troyan · 2019
Later among the works it cites.
On optimal ordering in the optimal stopping problem
Shipra Agrawal, Jay Sethuraman, and Xingyu Zhang · 2020
Closest in time.
Machine learning-powered iterative combinatorial auctions
Gianluca Brero, Benjamin Lubin, and Sven Seuken · 2020
Closest in time.
Reinforcement mechanism design: With applications to dynamic pricing in sponsored search auctions
Weiran Shen, Binghui Peng, Hanpeng Liu, Michael Zhang, Ruohan Qian, Yan Hong, Zhi Guo, Zongyao Ding, Pengjun Lu, and Pingzhong Tang · 2020
Closest in time.
The AI economist: Improving equality and productivity with ai-driven tax policies
Stephan Zheng, Alexander Trott, Sunil Srinivasa, Nikhil Naik, Melvin Gruesbeck, David C. Parkes, and Richard Socher · 2020
Closest in time.
Reinforcement learning of simple indirect mechanisms
Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, and Duncan Rheingans-Yoo · 2021
Closest in time.