Amy Greenwald

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 48

Top Venues

Publications

Michael P. Wellman, Karl Tuyls, Amy Greenwald
Empirical Game-Theoretic Analysis: A Survey. CoRR (2024)
Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh
Efficient Inverse Multiagent Learning. ICLR (2024)
Denizalp Goktas, Arjun Prakash, Amy Greenwald
Convex-Concave Zero-sum Markov Stackelberg Games. CoRR (2024)
John Randolph, Amy Greenwald, Denizalp Goktas
Banzhaf Power in Hierarchical Games. AAMAS (2024)
Jiayi Zhao, Denizalp Goktas, Amy Greenwald
Fisher Markets with Social Influence. CoRR (2023)
Jiayi Zhao, Denizalp Goktas, Amy Greenwald
Fisher Markets with Social Influence. AAAI (2023)
Denizalp Goktas, Arjun Prakash, Amy Greenwald
Convex-Concave Zero-Sum Stochastic Stackelberg Games. NeurIPS (2023)
Cyrus Cousins, Bhaskar Mishra, Enrique Areyan Viqueira, Amy Greenwald
Learning Properties in Simulation-Based Games. AAMAS (2023)
Denizalp Goktas, Jiayi Zhao, Amy Greenwald
Tâtonnement in Homothetic Fisher Markets. EC (2023)
Rigel Galgana, Takehiro Oyakawa, Amy Greenwald
Computing Boundary Crossing Probabilities of General Empirical Processes. ACDA (2023)
Denizalp Goktas, Jiayi Zhao, Amy Greenwald
Tâtonnement in Homothetic Fisher Markets. CoRR (2023)
Cyrus Cousins, Bhaskar Mishra, Enrique Areyan Viqueira, Amy Greenwald
Computational and Data Requirements for Learning Generic Properties of Simulation-Based Games. CoRR (2022)
Dustin Morrill, Esra'a Saleh, Michael Bowling, Amy Greenwald
Interpolating Between Softmax Policy Gradient and Neural Replicator Dynamics with Capped Implicit Exploration. CoRR (2022)
Denizalp Goktas, Jiayi Zhao, Amy Greenwald
Robust No-Regret Learning in Min-Max Stackelberg Games. AAMAS (2022)
Denizalp Goktas, Jiayi Zhao, Amy Greenwald
Robust No-Regret Learning in Min-Max Stackelberg Games. CoRR (2022)
Denizalp Goktas, Sadie Zhao, Amy Greenwald
Zero-Sum Stochastic Stackelberg Games. NeurIPS (2022)
Denizalp Goktas, Amy Greenwald
Gradient Descent Ascent in Min-Max Stackelberg Games. CoRR (2022)
Bhaskar Mishra, Cyrus Cousins, Amy Greenwald
Regret Pruning for Learning Equilibria in Simulation-Based Games. CoRR (2022)
Denizalp Goktas, Jiayi Zhao, Amy Greenwald
Zero-Sum Stochastic Stackelberg Games. CoRR (2022)
Denizalp Goktas, Amy Greenwald
Exploitability Minimization in Games and Beyond. NeurIPS (2022)
Denizalp Goktas, Amy Greenwald
Exploitability Minimization in Games and Beyond. CoRR (2022)
Denizalp Goktas, Amy Greenwald
Convex-Concave Min-Max Stackelberg Games. CoRR (2021)
Rigel Galgana, Amy Greenwald, Takehiro Oyakawa
A Dynamic Programming Algorithm to Compute Joint Distribution of Order Statistics on Graphs. CoRR (2021)
Denizalp Goktas, Enrique Areyan Viqueira, Amy Greenwald
Tâtonnement Beyond Constant Elasticity of Substitution. CoRR (2021)
Rigel Galgana, Cengke Shi, Amy Greenwald, Takehiro Oyakawa
A Dynamic Program for Computing the Joint Cumulative Distribution Function of Order Statistics. ACDA (2021)
Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald
Learning Competitive Equilibria in Noisy Combinatorial Markets. AAMAS (2021)
Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald
Learning Competitive Equilibria in Noisy Combinatorial Markets. CoRR (2021)
Denizalp Goktas, Enrique Areyan Viqueira, Amy Greenwald
A Consumer-Theoretic Characterization of Fisher Market Equilibria. WINE (2021)
Denizalp Goktas, Amy Greenwald
Convex-Concave Min-Max Stackelberg Games. NeurIPS (2021)
Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy Greenwald
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games. CoRR (2021)
Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy Greenwald, Michael Bowling
Hindsight and Sequential Rationality of Correlated Play. CoRR (2020)
Yasser Mohammad, Shinji Nakadai, Amy Greenwald
NegMAS: A Platform for Automated Negotiations. PRIMA (2020)
Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald
Improved Algorithms for Learning Equilibria in Simulation-Based Games. AAMAS (2020)
Enrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, Amy Greenwald
Empirical Mechanism Design: Designing Mechanisms from Data. UAI (2019)
Enrique Areyan Viqueira, Cyrus Cousins, Eli Upfal, Amy Greenwald
Learning Equilibria of Simulation-Based Games. CoRR (2019)
Yasser Mohammad, Enrique Areyan Viqueira, Nahum Alvarez Ayerza, Amy Greenwald, Shinji Nakadai, Satoshi Morinaga
Supply Chain Management World - A Benchmark Environment for Situated Negotiations. PRIMA (2019)
Gregory D. Hager, Ann W. Drobnis, Fei Fang, Rayid Ghani, Amy Greenwald, Terah Lyons, David C. Parkes, Jason Schultz, Suchi Saria, Stephen F. Smith, Milind Tambe
Artificial Intelligence for Social Good. CoRR (2019)
Enrique Areyan Viqueira, Amy Greenwald, Cyrus Cousins, Eli Upfal
Learning Simulation-Based Games from Data. AAMAS (2019)
Amy Greenwald, Jasper Lee, Takehiro Oyakawa
Fast Algorithms for Computing Interim Allocations in Single-Parameter Environments. PRIMA (2018)
Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
On Revenue-Maximizing Mechanisms Assuming Convex Costs. SAGT (2018)
Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
Simple vs Optimal Contests with Convex Costs. WWW (2018)
Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
Simple vs Optimal Mechanisms in Auctions with Convex Payments. CoRR (2017)
Enrique Areyan Viqueira, Amy Greenwald, Victor Naroditskiy
On Approximate Welfare- and Revenue-Maximizing Equilibria for Size-Interchangeable Bidders. AAMAS (2017)
Enrique Areyan Viqueira, Amy Greenwald, Victor Naroditskiy
On Approximate Welfare- and Revenue-Maximizing Equilibria for Size-Interchangeable Bidders. CoRR (2017)
Michael P. Wellman, Eric Sodomka, Amy Greenwald
Self-confirming price-prediction strategies for simultaneous one-shot auctions. Games Econ. Behav. 102 (2017)
Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
Optimal Auctions with Convex Perceived Payments. CoRR (2016)
Mark K. Ho, James MacGlashan, Amy Greenwald, Michael L. Littman, Elizabeth Hilliard, Carl Trimbach, Stephen Brawner, Josh Tenenbaum, Max Kleiman-Weiner, Joseph L. Austerweil
Feature-based Joint Planning and Norm Learning in Collaborative Games. CogSci (2016)
Enrique Areyan Viqueira, Amy Greenwald, Victor Naroditskiy, Daniels Collins
On Revenue-Maximizing Walrasian Equilibria for Size-Interchangeable Bidders. AMEC/TADA (2016)
Amy Greenwald, Seong Jae Lee, Victor Naroditskiy
RoxyBot-06: Stochastic Prediction and Optimization in TAC Travel. CoRR (2014)
Elizabeth M. Hilliard, Amy Greenwald, Victor Naroditskiy
An Algorithm for the Penalized Multiple Choice Knapsack Problem. ECAI (2014)
Geoffroy de Clippel, Victor Naroditskiy, Maria Polukarov, Amy Greenwald, Nicholas R. Jennings
Destroy to save. Games Econ. Behav. 86 (2014)
Amy Greenwald, Eric Sodomka, Eric Stix, Jeffrey Stix, David Storch
An Empirical Analysis of QuiBids' Penny Auctions. AMEC/TADA (2014)
Eric Sodomka, Elizabeth Hilliard, Michael L. Littman, Amy Greenwald
Coco-Q: Learning in Stochastic Games with Side Payments. ICML (3) (2013)
Brandon A. Mayer, Eric Sodomka, Amy Greenwald, Michael P. Wellman
Accounting for price dependencies in simultaneous sealed-bid auctions. EC (2013)
Amy Greenwald, Eric Sodomka, Eric Stix, Jeffrey Stix, David Storch
Empirical Analysis of Auctioneer Profitability in QuiBids Penny Auctions. AAAI Workshop: Trading Agent Design and Analysis (2013)
Brandon A. Mayer, Eric Sodomka, Amy Greenwald
The price of independence in simultaneous auctions. AAMAS (2013)
Brandon A. Mayer, Eric Sodomka, Amy Greenwald, Michael P. Wellman
Accounting for Price Dependencies in Simultaneous Sealed-Bid Auctions. AAAI Workshop: Trading Agent Design and Analysis (2013)
John R. Wicks, Amy Greenwald
An Algorithm for Computing Stochastically Stable Distributions with Applications to Multiagent Learning in Repeated Games CoRR (2012)
Amy Greenwald, Jiacui Li, Eric Sodomka
Approximating Equilibria in Sequential Auctions with Incomplete Information and Multi-Unit Demand. NIPS (2012)
Michael P. Wellman, Eric Sodomka, Amy Greenwald
Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions. UAI (2012)
Michael P. Wellman, Eric Sodomka, Amy Greenwald
Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions CoRR (2012)
Amy Greenwald, Justin A. Boyan
Bidding under Uncertainty: Theory and Experiments CoRR (2012)
Thomas Goff, Amy Greenwald, Elizabeth Hilliard, Wolfgang Ketter, Andrew Loomis, Eric Sodomka
JACK: A Java Auction Configuration Kit. AMEC/TADA (2012)
Mingyu Guo, Victor Naroditskiy, Vincent Conitzer, Amy Greenwald, Nicholas R. Jennings
Budget-Balanced and Nearly Efficient Randomized Mechanisms: Public Goods and beyond. WINE (2011)
Jordan Berg, Carleton Coffrin, Amy Greenwald, Eric Sodomka
Rank and Impression Estimation in a Stylized Model of Ad Auctions. AMEC/TADA (2010)
Jordan Berg, Amy Greenwald, Victor Naroditskiy, Eric Sodomka
A Knapsack-Based Approach to Bidding in Ad Auctions. ECAI (2010)
Amy Greenwald, Karthik N. Kannan, Ramayya Krishnan
On Evaluating Information Revelation Policies in Procurement Auctions: A Markov Decision Process Approach. Inf. Syst. Res. 21 (1) (2010)
Geoffroy de Clippel, Victor Naroditskiy, Amy Greenwald
Destroy to save. EC (2009)
Amy Greenwald, Seong Jae Lee, Victor Naroditskiy
RoxyBot-06: Stochastic Prediction and Optimization in TAC Travel. J. Artif. Intell. Res. 36 (2009)
Michael P. Wellman, Amy Greenwald, Peter Stone
Book announcement: autonomous bidding agents. SIGecom Exch. 7 (2) (2008)
Amy Greenwald, Victor Naroditskiy, Seong Jae Lee
Bidding Heuristics for Simultaneous Auctions: Lessons from TAC Travel. AMEC/TADA (2008)
Amy Greenwald, Zheng Li, Warren Schudy
More Efficient Internal-Regret-Minimizing Algorithms. COLT (2008)
Geoffrey J. Gordon, Amy Greenwald, Casey Marks
No-regret learning in convex games. ICML (2008)
John R. Wicks, Amy Greenwald
More efficient parallel computation of pagerank. SIGIR (2007)
Victor Naroditskiy, Amy Greenwald
Using Iterated Best-Response to Find Bayes-Nash Equilibria in Auctions. AAAI (2007)
Seong Jae Lee, Amy Greenwald, Victor Naroditskiy
RoxyBot-06: An (SAA)2 TAC Travel Agent. IJCAI (2007)
Amy Greenwald, Michael L. Littman
Introduction to the special issue on learning and computational game theory. Mach. Learn. 67 (1-2) (2007)
John R. Wicks, Amy Greenwald
Parallelizing the Computation of PageRank. WAW (2007)
Ashish Arora, Amy Greenwald, Karthik N. Kannan, Ramayya Krishnan
Effects of Information-Revelation Policies Under Market-Structure Uncertainty. Manag. Sci. 53 (8) (2007)
Martin Zinkevich, Amy Greenwald, Michael L. Littman
A hierarchy of prescriptive goals for multiagent learning. Artif. Intell. 171 (7) (2007)
Amy Greenwald, Victor Naroditskiy, Tyler Odean, Mauricio Ramirez, Eric Sodomka, Joe Zimmerman, Clark Cutler
Marginal Bidding: An Application of the Equimarginal Principle to Bidding in TAC SCM. AMEC/TADA (2007)
Amy Greenwald
Editor's introduction. SIGecom Exch. 6 (1) (2006)
Amy Greenwald
Editor's introduction. SIGecom Exch. 5 (5) (2006)
John R. Wicks, Amy Greenwald
A Quotient Construction on Markov Chains with Applications to the Theory of Generalized Simulated Annealing. AI&M (2006)
Amy Greenwald, Zheng Li, Casey Marks
Bounds for Regret-Matching Algorithms. AI&M (2006)
Amy Greenwald, Victor Naroditskiy
Heuristics for the deterministic bidding problem. SIGecom Exch. 6 (1) (2006)
Martin Zinkevich, Amy Greenwald, Michael L. Littman
Cyclic Equilibria in Markov Games. NIPS (2005)
John R. Wicks, Amy Greenwald
An Algorithm for Computing Stochastically Stable Distributions with Applications to Multiagent Learning in Repeated Games. UAI (2005)
Peter Stone, Amy Greenwald
The First International Trading Agent Competition: Autonomous Bidding Agents. Electron. Commer. Res. 5 (2) (2005)
Amy Greenwald, Bryan Guillemette, Victor Naroditskiy, Michael Carl Tschantz
Scaling Up the Sample Average Approximation Method for Stochastic Optimization with Applications to Trading Agents. AMEC@AAMAS/TADA@IJCAI (2005)
Amy Greenwald
Editor's introduction. SIGecom Exch. 5 (3) (2005)
Mary Ellen Zurko, Amy Greenwald
Foreword. Electron. Commer. Res. 5 (1) (2005)
Amy Greenwald, Justin A. Boyan
Bidding under Uncertainty: Theory and Experiments. UAI (2004)
Michael Benisch, Amy Greenwald, Ioanna Grypari, Roger Lederman, Victor Naroditskiy, Michael Carl Tschantz
Botticelli: a supply chain management agent designed to optimize under uncertainty. SIGecom Exch. 4 (3) (2004)
Michael Benisch, Amy Greenwald, Ioanna Grypari, Roger Lederman, Victor Naroditskiy, Michael Carl Tschantz
Botticelli: A Supply Chain Management Agent. AAMAS (2004)
Amy Greenwald
Editor's introduction. SIGecom Exch. 5 (1) (2004)
Amy Greenwald
Editor's introduction. SIGecom Exch. 4 (3) (2004)
Michael Benisch, Amy Greenwald, Victor Naroditskiy, Michael Carl Tschantz
A stochastic programming approach to scheduling in TAC SCM. EC (2004)
Amy Greenwald
Editor's introduction. SIGecom Exch. 5 (2) (2004)
Amy Greenwald, Amir Jafari
A General Class of No-Regret Learning Algorithms and Game-Theoretic Equilibria. COLT (2003)

Amy Greenwald.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Amy Greenwald