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ORCIDAmy Greenwald
Amy R. Greenwald
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- affiliation: Brown University, Providence, USA
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2020 – today
- 2024
[c72]John Randolph, Amy Greenwald, Denizalp Goktas:
Banzhaf Power in Hierarchical Games. AAMAS 2024: 2432-2434- [c71]Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh:
Efficient Inverse Multiagent Learning. ICLR 2024 - [i27]Denizalp Goktas, Arjun Prakash, Amy Greenwald
:
Convex-Concave Zero-sum Markov Stackelberg Games. CoRR abs/2401.12437 (2024) - [i26]Michael P. Wellman, Karl Tuyls, Amy Greenwald:
Empirical Game-Theoretic Analysis: A Survey. CoRR abs/2403.04018 (2024) - 2023
- [c70]Jiayi Zhao, Denizalp Goktas, Amy Greenwald:
Fisher Markets with Social Influence. AAAI 2023: 5900-5909 - [c69]Rigel Galgana, Takehiro Oyakawa, Amy Greenwald:
Computing Boundary Crossing Probabilities of General Empirical Processes. ACDA 2023: 237-246 - [c68]Cyrus Cousins, Bhaskar Mishra, Enrique Areyan Viqueira, Amy Greenwald:
Learning Properties in Simulation-Based Games. AAMAS 2023: 272-280 - [c67]Denizalp Goktas, Arjun Prakash, Amy Greenwald:
Convex-Concave Zero-Sum Stochastic Stackelberg Games. NeurIPS 2023 - [c66]Denizalp Goktas, Jiayi Zhao, Amy Greenwald:
Tâtonnement in Homothetic Fisher Markets. EC 2023: 760-781 - [i25]Jiayi Zhao, Denizalp Goktas, Amy Greenwald:
Fisher Markets with Social Influence. CoRR abs/2303.06307 (2023) - [i24]Denizalp Goktas, Jiayi Zhao, Amy Greenwald:
Tâtonnement in Homothetic Fisher Markets. CoRR abs/2306.04890 (2023) - 2022
- [c65]Denizalp Goktas, Jiayi Zhao, Amy Greenwald:
Robust No-Regret Learning in Min-Max Stackelberg Games. AAMAS 2022: 543-552 - [c64]Denizalp Goktas, Amy Greenwald:
Exploitability Minimization in Games and Beyond. NeurIPS 2022 - [c63]Denizalp Goktas, Sadie Zhao, Amy Greenwald:
Zero-Sum Stochastic Stackelberg Games. NeurIPS 2022 - [i23]Denizalp Goktas, Jiayi Zhao, Amy Greenwald:
Robust No-Regret Learning in Min-Max Stackelberg Games. CoRR abs/2203.14126 (2022) - [i22]Dustin Morrill, Esra'a Saleh, Michael Bowling, Amy Greenwald:
Interpolating Between Softmax Policy Gradient and Neural Replicator Dynamics with Capped Implicit Exploration. CoRR abs/2206.02036 (2022) - [i21]Cyrus Cousins, Bhaskar Mishra, Enrique Areyan Viqueira, Amy Greenwald:
Computational and Data Requirements for Learning Generic Properties of Simulation-Based Games. CoRR abs/2208.06400 (2022) - [i20]Denizalp Goktas, Amy Greenwald:
Gradient Descent Ascent in Min-Max Stackelberg Games. CoRR abs/2208.09690 (2022) - [i19]Denizalp Goktas, Amy Greenwald:
Exploitability Minimization in Games and Beyond. CoRR abs/2210.10207 (2022) - [i18]Denizalp Goktas, Jiayi Zhao, Amy Greenwald:
Zero-Sum Stochastic Stackelberg Games. CoRR abs/2211.13847 (2022) - [i17]Bhaskar Mishra, Cyrus Cousins, Amy Greenwald:
Regret Pruning for Learning Equilibria in Simulation-Based Games. CoRR abs/2211.16670 (2022) - 2021
- [c62]Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy R. Greenwald, Michael Bowling:
Hindsight and Sequential Rationality of Correlated Play. AAAI 2021: 5584-5594 - [c61]Rigel Galgana, Cengke Shi, Amy Greenwald, Takehiro Oyakawa:
A Dynamic Program for Computing the Joint Cumulative Distribution Function of Order Statistics. ACDA 2021: 160-170 - [c60]Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald:
Learning Competitive Equilibria in Noisy Combinatorial Markets. AAMAS 2021: 1446-1448 - [c59]Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy R. Greenwald:
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games. ICML 2021: 7818-7828 - [c58]Denizalp Goktas, Amy Greenwald:
Convex-Concave Min-Max Stackelberg Games. NeurIPS 2021: 2991-3003 - [c57]Denizalp Goktas, Enrique Areyan Viqueira, Amy Greenwald:
A Consumer-Theoretic Characterization of Fisher Market Equilibria. WINE 2021: 334-351 - [i16]Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald:
Learning Competitive Equilibria in Noisy Combinatorial Markets. CoRR abs/2101.09551 (2021) - [i15]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 abs/2102.06973 (2021) - [i14]Denizalp Goktas, Enrique Areyan Viqueira, Amy Greenwald:
Tâtonnement Beyond Constant Elasticity of Substitution. CoRR abs/2107.08153 (2021) - [i13]Denizalp Goktas, Amy Greenwald:
Convex-Concave Min-Max Stackelberg Games. CoRR abs/2110.05192 (2021) - [i12]Dustin Morrill, Amy R. Greenwald, Michael Bowling:
The Partially Observable History Process. CoRR abs/2111.08102 (2021) - [i11]Rigel Galgana, Amy Greenwald, Takehiro Oyakawa:
A Dynamic Programming Algorithm to Compute Joint Distribution of Order Statistics on Graphs. CoRR abs/2111.10939 (2021) - 2020
- [c56]Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald:
Improved Algorithms for Learning Equilibria in Simulation-Based Games. AAMAS 2020: 79-87 - [c55]Yasser Mohammad, Shinji Nakadai, Amy Greenwald:
NegMAS: A Platform for Automated Negotiations. PRIMA 2020: 343-351 - [i10]Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy Greenwald, Michael Bowling:
Hindsight and Sequential Rationality of Correlated Play. CoRR abs/2012.05874 (2020)
2010 – 2019
- 2019
- [c54]Enrique Areyan Viqueira, Amy Greenwald, Cyrus Cousins, Eli Upfal:
Learning Simulation-Based Games from Data. AAMAS 2019: 1778-1780 - [c53]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: 153-169 - [c52]Enrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, Amy Greenwald:
Empirical Mechanism Design: Designing Mechanisms from Data. UAI 2019: 1094-1104 - [i9]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 abs/1901.05406 (2019) - [i8]Enrique Areyan Viqueira, Cyrus Cousins, Eli Upfal, Amy Greenwald:
Learning Equilibria of Simulation-Based Games. CoRR abs/1905.13379 (2019) - 2018
- [c51]Amy Greenwald, Jasper Lee, Takehiro Oyakawa:
Fast Algorithms for Computing Interim Allocations in Single-Parameter Environments. PRIMA 2018: 194-209 - [c50]Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis:
On Revenue-Maximizing Mechanisms Assuming Convex Costs. SAGT 2018: 113-124 - [c49]Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis:
Simple vs Optimal Contests with Convex Costs. WWW 2018: 1429-1438 - 2017
- [j26]Michael P. Wellman, Eric Sodomka, Amy Greenwald:
Self-confirming price-prediction strategies for simultaneous one-shot auctions. Games Econ. Behav. 102: 339-372 (2017) - [c48]Enrique Areyan Viqueira, Amy Greenwald, Victor Naroditskiy:
On Approximate Welfare- and Revenue-Maximizing Equilibria for Size-Interchangeable Bidders. AAMAS 2017: 1466-1468 - [i7]Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis:
Simple vs Optimal Mechanisms in Auctions with Convex Payments. CoRR abs/1702.06062 (2017) - [i6]Enrique Areyan Viqueira, Amy Greenwald, Victor Naroditskiy:
On Approximate Welfare- and Revenue-Maximizing Equilibria for Size-Interchangeable Bidders. CoRR abs/1708.03097 (2017) - 2016
- [c47]Enrique Areyan Viqueira, Amy Greenwald, Victor Naroditskiy, Daniels Collins:
On Revenue-Maximizing Walrasian Equilibria for Size-Interchangeable Bidders. AMEC/TADA 2016: 19-34 - [c46]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 - [i5]Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis:
Optimal Auctions with Convex Perceived Payments. CoRR abs/1601.07163 (2016) - 2014
- [j25]Geoffroy de Clippel, Victor Naroditskiy, Maria Polukarov, Amy Greenwald, Nicholas R. Jennings:
Destroy to save. Games Econ. Behav. 86: 392-404 (2014) - [c45]Amy Greenwald, Eric Sodomka, Eric Stix, Jeffrey Stix, David Storch:
An Empirical Analysis of QuiBids' Penny Auctions. AMEC/TADA 2014: 56-69 - [c44]Elizabeth M. Hilliard, Amy Greenwald, Victor Naroditskiy:
An Algorithm for the Penalized Multiple Choice Knapsack Problem. ECAI 2014: 1025-1026 - [i4]Amy Greenwald, Seong Jae Lee, Victor Naroditskiy:
RoxyBot-06: Stochastic Prediction and Optimization in TAC Travel. CoRR abs/1401.3829 (2014) - 2013
- [c43]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 - [c42]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 - [c41]Brandon A. Mayer, Eric Sodomka, Amy Greenwald:
The price of independence in simultaneous auctions. AAMAS 2013: 1227-1228 - [c40]Eric Sodomka, Elizabeth Hilliard, Michael L. Littman, Amy Greenwald:
Coco-Q: Learning in Stochastic Games with Side Payments. ICML (3) 2013: 1471-1479 - [c39]Brandon A. Mayer, Eric Sodomka, Amy Greenwald, Michael P. Wellman:
Accounting for price dependencies in simultaneous sealed-bid auctions. EC 2013: 679-696 - 2012
- [c38]Thomas Goff, Amy Greenwald, Elizabeth Hilliard, Wolfgang Ketter, Andrew Loomis, Eric Sodomka:
JACK: A Java Auction Configuration Kit. AMEC/TADA 2012: 45-60 - [c37]Amy Greenwald, Jiacui Li, Eric Sodomka:
Approximating Equilibria in Sequential Auctions with Incomplete Information and Multi-Unit Demand. NIPS 2012: 2330-2338 - [c36]Michael P. Wellman, Eric Sodomka, Amy Greenwald:
Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions. UAI 2012: 893-902 - [i3]John R. Wicks, Amy Greenwald:
An Algorithm for Computing Stochastically Stable Distributions with Applications to Multiagent Learning in Repeated Games. CoRR abs/1207.1424 (2012) - [i2]Amy Greenwald, Justin A. Boyan:
Bidding under Uncertainty: Theory and Experiments. CoRR abs/1207.4108 (2012) - [i1]Michael P. Wellman, Eric Sodomka, Amy Greenwald:
Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions. CoRR abs/1210.4915 (2012) - 2011
- [c35]Mingyu Guo, Victor Naroditskiy, Vincent Conitzer, Amy Greenwald, Nicholas R. Jennings:
Budget-Balanced and Nearly Efficient Randomized Mechanisms: Public Goods and beyond. WINE 2011: 158-169 - 2010
- [j24]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): 15-36 (2010) - [c34]Jordan Berg, Carleton Coffrin, Amy Greenwald, Eric Sodomka:
Rank and Impression Estimation in a Stylized Model of Ad Auctions. AMEC/TADA 2010: 1-18 - [c33]Jordan Berg, Amy Greenwald, Victor Naroditskiy, Eric Sodomka:
A Knapsack-Based Approach to Bidding in Ad Auctions. ECAI 2010: 1013-1014
2000 – 2009
- 2009
- [j23]Amy Greenwald, Seong Jae Lee, Victor Naroditskiy:
RoxyBot-06: Stochastic Prediction and Optimization in TAC Travel. J. Artif. Intell. Res. 36: 513-546 (2009) - [c32]Geoffroy de Clippel, Victor Naroditskiy, Amy Greenwald:
Destroy to save. EC 2009: 207-214 - 2008
- [j22]Michael P. Wellman, Amy Greenwald, Peter Stone:
Book announcement: autonomous bidding agents. SIGecom Exch. 7(2) (2008) - [c31]Amy Greenwald, Victor Naroditskiy, Seong Jae Lee:
Bidding Heuristics for Simultaneous Auctions: Lessons from TAC Travel. AMEC/TADA 2008: 131-146 - [c30]Amy Greenwald, Zheng Li, Warren Schudy:
More Efficient Internal-Regret-Minimizing Algorithms. COLT 2008: 239-250 - [c29]Geoffrey J. Gordon, Amy Greenwald, Casey Marks:
No-regret learning in convex games. ICML 2008: 360-367 - 2007
- [b2]Michael P. Wellman, Amy Greenwald, Peter Stone:
Autonomous bidding agents - strategies and lessons from the trading agent competition. MIT Press 2007, ISBN 978-0-262-23260-9, pp. I-XI, 1-238 - [j21]Martin Zinkevich, Amy Greenwald, Michael L. Littman:
A hierarchy of prescriptive goals for multiagent learning. Artif. Intell. 171(7): 440-447 (2007) - [j20]Ashish Arora, Amy Greenwald, Karthik N. Kannan, Ramayya Krishnan:
Effects of Information-Revelation Policies Under Market-Structure Uncertainty. Manag. Sci. 53(8): 1234-1248 (2007) - [j19]Amy Greenwald, Michael L. Littman:
Introduction to the special issue on learning and computational game theory. Mach. Learn. 67(1-2): 3-6 (2007) - [c28]Victor Naroditskiy, Amy Greenwald:
Using Iterated Best-Response to Find Bayes-Nash Equilibria in Auctions. AAAI 2007: 1894-1895 - [c27]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: 217-239 - [c26]Seong Jae Lee, Amy Greenwald, Victor Naroditskiy:
RoxyBot-06: An (SAA)2 TAC Travel Agent. IJCAI 2007: 1378-1383 - [c25]John R. Wicks, Amy Greenwald:
More efficient parallel computation of pagerank. SIGIR 2007: 861-862 - [c24]John R. Wicks, Amy Greenwald:
Parallelizing the Computation of PageRank. WAW 2007: 202-208 - 2006
- [j18]Amy Greenwald:
Editor's introduction. SIGecom Exch. 5(5) (2006) - [j17]Amy Greenwald:
Editor's introduction. SIGecom Exch. 6(1) (2006) - [j16]Amy Greenwald, Victor Naroditskiy:
Heuristics for the deterministic bidding problem. SIGecom Exch. 6(1): 35-44 (2006) - [c23]Amy Greenwald, Zheng Li, Casey Marks:
Bounds for Regret-Matching Algorithms. AI&M 2006 - [c22]John R. Wicks, Amy Greenwald:
A Quotient Construction on Markov Chains with Applications to the Theory of Generalized Simulated Annealing. AI&M 2006 - 2005
- [j15]Mary Ellen Zurko, Amy Greenwald:
Foreword. Electron. Commer. Res. 5(1): 5-6 (2005) - [j14]Peter Stone, Amy Greenwald:
The First International Trading Agent Competition: Autonomous Bidding Agents. Electron. Commer. Res. 5(2): 229-265 (2005) - [j13]Amy Greenwald:
Editor's introduction. SIGecom Exch. 5(3) (2005) - [c21]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: 187-199 - [c20]Martin Zinkevich, Amy Greenwald, Michael L. Littman:
Cyclic Equilibria in Markov Games. NIPS 2005: 1641-1648 - [c19]John R. Wicks, Amy Greenwald:
An Algorithm for Computing Stochastically Stable Distributions with Applications to Multiagent Learning in Repeated Games. UAI 2005: 623-632 - 2004
- [j12]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): 29-37 (2004) - [j11]Amy Greenwald:
Editor's introduction. SIGecom Exch. 4(3) (2004) - [j10]Amy Greenwald:
Editor's introduction. SIGecom Exch. 5(1) (2004) - [j9]Amy Greenwald:
Editor's introduction. SIGecom Exch. 5(2) (2004) - [c18]Michael Benisch, Amy Greenwald, Ioanna Grypari, Roger Lederman, Victor Naroditskiy, Michael Carl Tschantz:
Botticelli: A Supply Chain Management Agent. AAMAS 2004: 1174-1181 - [c17]Michael Benisch, Amy Greenwald, Victor Naroditskiy, Michael Carl Tschantz:
A stochastic programming approach to scheduling in TAC SCM. EC 2004: 152-159 - [c16]Amy Greenwald, Justin A. Boyan:
Bidding under Uncertainty: Theory and Experiments. UAI 2004: 209-216 - 2003
- [j8]Amy Greenwald:
The 2002 Trading Agent Competition: An Overview of Agent Strategies. AI Mag. 24(1): 83-91 (2003) - [j7]Joan Morris DiMicco, Pattie Maes, Amy Greenwald:
Learning Curve: A Simulation-Based Approach to Dynamic Pricing. Electron. Commer. Res. 3(3-4): 245-276 (2003) - [j6]Michael P. Wellman, Amy Greenwald, Peter Stone, Peter R. Wurman:
The 2001 Trading Agent Competition. Electron. Mark. 13(1): 4-12 (2003) - [j5]Amy Greenwald, Nicholas R. Jennings, Peter Stone:
Guest Editors' Introduction: Agents and Markets. IEEE Intell. Syst. 18(6): 12-14 (2003) - [c15]Amy Greenwald, Amir Jafari:
A General Class of No-Regret Learning Algorithms and Game-Theoretic Equilibria. COLT 2003: 2-12 - [c14]Amy Greenwald, Karthik N. Kannan, Ramayya Krishnan:
A Computational Approach to Compare Information Revelation Policies. ICIS 2003: 706-719 - [c13]Amy Greenwald, Keith Hall:
Correlated Q-Learning. ICML 2003: 242-249 - [c12]Amy Greenwald:
Bidding Marginal Utility in Simultaneous Auctions. IJCAI 2003: 1463-1464 - 2002
- [j4]Jeffrey O. Kephart, Amy Greenwald:
Shopbot Economics. Auton. Agents Multi Agent Syst. 5(3): 255-287 (2002) - [c11]Michael P. Wellman, Amy Greenwald, Peter Stone, Peter R. Wurman:
The 2001 Trading Agent Competition. AAAI/IAAI 2002: 935-942 - 2001
- [j3]Amy Greenwald, Eric J. Friedman, Scott Shenker:
Learning in Network Contexts: Experimental Results from Simulations. Games Econ. Behav. 35(1-2): 80-123 (2001) - [j2]Amy Greenwald, Peter Stone:
Autonomous Bidding Agents in the Trading Agent Competition. IEEE Internet Comput. 5(2): 52-60 (2001) - [c10]Amy Greenwald, Jeffrey O. Kephart:
Probabilistic pricebots. Agents 2001: 560-567 - [c9]Amir Jafari, Amy Greenwald, David Gondek, Gunes Ercal:
On No-Regret Learning, Fictitious Play, and Nash Equilibrium. ICML 2001: 226-233 - [c8]Joan Morris DiMicco, Amy Greenwald, Pattie Maes:
Dynamic pricing strategies under a finite time horizon. EC 2001: 95-104 - [c7]Amy Greenwald, Justin A. Boyan:
Bidding algorithms for simultaneous auctions. EC 2001: 115-124 - [c6]Justin A. Boyan, Amy Greenwald:
Bid determination in simultaneous actions an agent architecture. EC 2001: 210-212 - 2000
- [j1]Jeffrey O. Kephart, James E. Hanson, Amy Greenwald:
Dynamic pricing by software agents. Comput. Networks 32(6): 731-752 (2000)
1990 – 1999
- 1999
- [b1]