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ORCIDMichael P. Wellman
Michael Paul Wellman
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- affiliation: University of Michigan, Ann Arbor, USA
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2020 – today
- 2023
[c161]Yongzhao Wang, Michael P. Wellman:
Empirical Game-Theoretic Analysis for Mean Field Games. AAMAS 2023: 1025-1033- [c160]Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Kate Larson, Yoram Bachrach, Michael P. Wellman, Paul Muller:
Search-Improved Game-Theoretic Multiagent Reinforcement Learning in General and Negotiation Games. AAMAS 2023: 2445-2447 - [c159]Yongzhao Wang, Michael P. Wellman:
Regularization for Strategy Exploration in Empirical Game-Theoretic Analysis. AAMAS 2023: 2484-2486 - [c158]Yongzhao Wang, Michael P. Wellman:
Game Model Learning for Mean Field Games. AAMAS 2023: 2905-2907 - [i41]Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Paul Muller, Kate Larson, Yoram Bachrach, Michael P. Wellman:
Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning. CoRR abs/2302.00797 (2023) - [i40]Christine Konicki, Mithun Chakraborty, Michael P. Wellman:
Exploiting Extensive-Form Structure in Empirical Game-Theoretic Analysis. CoRR abs/2302.01366 (2023) - [i39]Yongzhao Wang, Michael P. Wellman:
Regularization for Strategy Exploration in Empirical Game-Theoretic Analysis. CoRR abs/2302.04928 (2023) - [i38]Max Olan Smith, Michael P. Wellman:
Co-Learning Empirical Games and World Models. CoRR abs/2305.14223 (2023) - 2022
- [c157]Yongzhao Wang, Qiurui Ma, Michael P. Wellman:
Evaluating Strategy Exploration in Empirical Game-Theoretic Analysis. AAMAS 2022: 1346-1354 - [c156]Christine Konicki, Mithun Chakraborty, Michael P. Wellman:
Exploiting Extensive-Form Structure in Empirical Game-Theoretic Analysis. WINE 2022: 132-149 - 2021
- [j72]Xintong Wang
, Christopher Hoang, Yevgeniy Vorobeychik, Michael P. Wellman:
Spoofing the Limit Order Book: A Strategic Agent-Based Analysis. Games 12(2): 46 (2021) - [c155]Zun Li, Michael P. Wellman:
Evolution Strategies for Approximate Solution of Bayesian Games. AAAI 2021: 5531-5540 - [c154]Katherine Mayo, Michael P. Wellman:
A Strategic Analysis of Portfolio Compression. AAMAS 2021: 1599-1601 - [c153]Katherine Mayo, Michael P. Wellman:
A strategic analysis of portfolio compression. ICAIF 2021: 20:1-20:8 - [c152]Katherine Mayo, Shaily Fozdar, Michael P. Wellman:
An agent-based model of strategic adoption of real-time payments. ICAIF 2021: 45:1-45:9 - [c151]Megan Shearer, David Byrd, Tucker Hybinette Balch, Michael P. Wellman:
Stability effects of arbitrage in exchange traded funds: an agent-based model. ICAIF 2021: 49:1-49:9 - [c150]Max Olan Smith, Thomas Anthony, Michael P. Wellman:
Iterative Empirical Game Solving via Single Policy Best Response. ICLR 2021 - [c149]Yongzhao Wang, Arunesh Sinha, Sky Ch-Wang, Michael P. Wellman:
Building Action Sets in a Deep Reinforcement Learner. ICMLA 2021: 484-489 - [c148]Xintong Wang, David M. Pennock, Nikhil R. Devanur, David M. Rothschild, Biaoshuai Tao, Michael P. Wellman:
Designing a Combinatorial Financial Options Market. EC 2021: 864-883 - [i37]Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael P. Wellman, Yevgeniy Vorobeychik:
A Game-Theoretic Approach for Hierarchical Policy-Making. CoRR abs/2102.10646 (2021) - [i36]Yongzhao Wang, Qiurui Ma, Michael P. Wellman:
Evaluating Strategy Exploration in Empirical Game-Theoretic Analysis. CoRR abs/2105.10423 (2021) - [i35]Max Olan Smith, Thomas Anthony, Michael P. Wellman:
Iterative Empirical Game Solving via Single Policy Best Response. CoRR abs/2106.01901 (2021) - [i34]Xintong Wang, David M. Pennock, Nikhil R. Devanur, David M. Rothschild, Biaoshuai Tao, Michael P. Wellman:
Designing a Combinatorial Financial Options Market. CoRR abs/2109.06443 (2021) - [i33]Yongzhao Wang, Michael P. Wellman:
Empirical Game-Theoretic Analysis in Mean Field Games. CoRR abs/2112.00900 (2021) - 2020
- [j71]Stefano V. Albrecht, Peter Stone, Michael P. Wellman:
Special issue on autonomous agents modelling other agents: Guest editorial. Artif. Intell. 285: 103292 (2020) - [c147]Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, Michael P. Wellman:
Generating Realistic Stock Market Order Streams. AAAI 2020: 727-734 - [c146]Zun Li, Michael P. Wellman:
Structure Learning for Approximate Solution of Many-Player Games. AAAI 2020: 2119-2127 - [c145]Xintong Wang, Christopher Hoang, Michael P. Wellman:
Learning-based trading strategies in the face of market manipulation. ICAIF 2020: 25:1-25:8 - [c144]Xintong Wang, Michael P. Wellman:
Market Manipulation: An Adversarial Learning Framework for Detection and Evasion. IJCAI 2020: 4626-4632 - [e7]Sushil Jajodia, George Cybenko, V. S. Subrahmanian, Vipin Swarup, Cliff Wang, Michael P. Wellman:
Adaptive Autonomous Secure Cyber Systems. Springer 2020, ISBN 978-3-030-33431-4 [contents] - [i32]Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, Michael P. Wellman:
Generating Realistic Stock Market Order Streams. CoRR abs/2006.04212 (2020) - [i31]Max Olan Smith, Thomas Anthony, Yongzhao Wang, Michael P. Wellman:
Learning to Play against Any Mixture of Opponents. CoRR abs/2009.14180 (2020)
2010 – 2019
- 2019
- [j70]Iyad Rahwan, Manuel Cebrián, Nick Obradovich, Josh C. Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, Nicholas A. Christakis, Iain D. Couzin, Matthew O. Jackson, Nicholas R. Jennings, Ece Kamar, Isabel M. Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C. Parkes, Alex 'Sandy' Pentland, Margaret E. Roberts, Azim Shariff, Joshua B. Tenenbaum, Michael P. Wellman:
Machine behaviour. Nat. 568(7753): 477-486 (2019) - [c143]Thanh Hong Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman:
Deception in Finitely Repeated Security Games. AAAI 2019: 2133-2140 - [c142]Arunesh Sinha, Michael P. Wellman:
Incentivizing Collaboration in a Competition. AAMAS 2019: 556-564 - [c141]Mason Wright, Yongzhao Wang, Michael P. Wellman:
Iterated Deep Reinforcement Learning in Games: History-Aware Training for Improved Stability. EC 2019: 617-636 - [c140]Frank Cheng, Yagil Engel, Michael P. Wellman:
Cap-and-Trade Emissions Regulation: A Strategic Analysis. IJCAI 2019: 187-193 - [p3]George Cybenko, Michael P. Wellman, Peng Liu, Minghui Zhu:
Overview of Control and Game Theory in Adaptive Cyber Defenses. Adversarial and Uncertain Reasoning for Adaptive Cyber Defense 2019: 1-11 - [p2]Hamidreza Tavafoghi, Yi Ouyang, Demosthenis Teneketzis, Michael P. Wellman:
Game Theoretic Approaches to Cyber Security: Challenges, Results, and Open Problems. Adversarial and Uncertain Reasoning for Adaptive Cyber Defense 2019: 29-53 - [p1]Michael P. Wellman, Thanh Hong Nguyen, Mason Wright:
Empirical Game-Theoretic Methods for Adaptive Cyber-Defense. Adversarial and Uncertain Reasoning for Adaptive Cyber Defense 2019: 112-128 - [e6]Sushil Jajodia, George Cybenko, Peng Liu, Cliff Wang, Michael P. Wellman:
Adversarial and Uncertain Reasoning for Adaptive Cyber Defense - Control- and Game-Theoretic Approaches to Cyber Security. Lecture Notes in Computer Science 11830, Springer 2019, ISBN 978-3-030-30718-9 [contents] - 2018
- [j69]Thanh Hai Nguyen, Mason Wright, Michael P. Wellman, Satinder Singh:
Multistage Attack Graph Security Games: Heuristic Strategies, with Empirical Game-Theoretic Analysis. Secur. Commun. Networks 2018: 2864873:1-2864873:28 (2018) - [c139]Thanh Hong Nguyen, Michael P. Wellman, Arunesh Sinha:
Deceitful Attacks in Security Games. AAAI Workshops 2018: 260-267 - [c138]Mason Wright, Michael P. Wellman:
Evaluating the Stability of Non-Adaptive Trading in Continuous Double Auctions: A Reinforcement Learning Approach. AAAI Workshops 2018: 317-324 - [c137]Bryce Wiedenbeck, Fengjun Yang, Michael P. Wellman:
A Regression Approach for Modeling Games With Many Symmetric Players. AAAI 2018: 1266-1273 - [c136]Mason Wright, Michael P. Wellman:
Evaluating the Stability of Non-Adaptive Trading in Continuous Double Auctions. AAMAS 2018: 614-622 - [c135]Nicolas Papernot, Patrick D. McDaniel, Arunesh Sinha, Michael P. Wellman:
SoK: Security and Privacy in Machine Learning. EuroS&P 2018: 399-414 - [c134]Megan Shearer, Michael P. Wellman:
Incentivizing Rider Time-Shift in a Multi-Leg Public Transportation System. ATT@IJCAI 2018: 86-93 - [c133]Xintong Wang, Yevgeniy Vorobeychik, Michael P. Wellman:
A Cloaking Mechanism to Mitigate Market Manipulation. IJCAI 2018: 541-547 - 2017
- [j68]Michael P. Wellman, Eric Sodomka, Amy Greenwald:
Self-confirming price-prediction strategies for simultaneous one-shot auctions. Games Econ. Behav. 102: 339-372 (2017) - [j67]Elaine Wah, Mason Wright, Michael P. Wellman:
Welfare Effects of Market Making in Continuous Double Auctions. J. Artif. Intell. Res. 59: 613-650 (2017) - [j66]Michael P. Wellman, Uday Rajan:
Ethical Issues for Autonomous Trading Agents. Minds Mach. 27(4): 609-624 (2017) - [c132]Thanh Hong Nguyen, Michael P. Wellman, Satinder Singh:
A Stackelberg Game Model for Botnet Traffic Exfiltration. AAAI Workshops 2017 - [c131]Xintong Wang, Michael Paul Wellman:
Spoofing the Limit Order Book: An Agent-Based Model. AAAI Workshops 2017 - [c130]Xintong Wang, Michael P. Wellman:
Spoofing the Limit Order Book: An Agent-Based Model. AAMAS 2017: 651-659 - [c129]Thanh Hai Nguyen, Mason Wright, Michael P. Wellman, Satinder Singh:
Multi-Stage Attack Graph Security Games: Heuristic Strategies, with Empirical Game-Theoretic Analysis. MTD@CCS 2017: 87-97 - [c128]Thanh Hai Nguyen, Michael P. Wellman, Satinder Singh:
A Stackelberg Game Model for Botnet Data Exfiltration. GameSec 2017: 151-170 - [c127]Frank Cheng, Michael P. Wellman:
Accounting for Strategic Response in an Agent-Based Model of Financial Regulation. EC 2017: 187-203 - [c126]Erik Brinkman, Michael P. Wellman:
Empirical Mechanism Design for Optimizing Clearing Interval in Frequent Call Markets. EC 2017: 205-221 - 2016
- [j65]Virginia Dignum, Nigel Gilbert, Michael P. Wellman:
Introduction to the special issue on autonomous agents for agent-based modeling. Auton. Agents Multi Agent Syst. 30(6): 1021-1022 (2016) - [j64]Michael P. Wellman:
Putting the agent in agent-based modeling. Auton. Agents Multi Agent Syst. 30(6): 1175-1189 (2016) - [j63]Elaine Wah, Michael P. Wellman:
Latency arbitrage in fragmented markets: A strategic agent-based analysis. Algorithmic Finance 5(3-4): 69-93 (2016) - [j62]Elaine Wah, Dylan Hurd, Michael P. Wellman:
Strategic Market Choice: Frequent Call Markets vs. Continuous Double Auctions for Fast and Slow Traders. EAI Endorsed Trans. Serious Games 3(10): e1 (2016) - [c125]Mason Wright, Sridhar Venkatesan, Massimiliano Albanese, Michael P. Wellman:
Moving Target Defense against DDoS Attacks: An Empirical Game-Theoretic Analysis. MTD@CCS 2016: 93-104 - [c124]Elaine Wah, Mason Wright, Michael P. Wellman:
Welfare Effects of Market Making in Continuous Double Auctions: Extended Abstract. IJCAI 2016: 4218-4222 - [c123]Frank Cheng, Junming Liu, Kareem Amin, Michael P. Wellman:
Strategic Payment Routing in Financial Credit Networks. EC 2016: 721-738 - [c122]Kareem Amin, Michael P. Wellman, Satinder Singh:
Gradient Methods for Stackelberg Games. UAI 2016 - [e5]Dale Schuurmans, Michael P. Wellman:
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA. AAAI Press 2016, ISBN 978-1-57735-760-5 [contents] - [i30]Nicolas Papernot, Patrick D. McDaniel, Arunesh Sinha, Michael P. Wellman:
Towards the Science of Security and Privacy in Machine Learning. CoRR abs/1611.03814 (2016) - 2015
- [j61]Pranav Dandekar, Ashish Goel, Michael P. Wellman, Bryce Wiedenbeck:
Strategic Formation of Credit Networks. ACM Trans. Internet Techn. 15(1): 3:1-3:41 (2015) - [c121]Elaine Wah, Michael P. Wellman:
Welfare Effects of Market Making in Continuous Double Auctions. AAMAS 2015: 57-66 - [c120]Bryce Wiedenbeck, Michael P. Wellman:
Learning Payoffs in Large Symmetric Games. AAMAS 2015: 1881-1882 - [c119]Achintya Prakash, Michael P. Wellman:
Empirical Game-Theoretic Analysis for Moving Target Defense. MTD@CCS 2015: 57-65 - 2014
- [c118]Erik Brinkman, Michael P. Wellman, Scott E. Page:
Signal structure and strategic information acquisition: deliberative auctions with interdependent values. AAMAS 2014: 229-236 - [c117]Bryce Wiedenbeck, Ben-Alexander Cassell, Michael P. Wellman:
Bootstrap statistics for empirical games. AAMAS 2014: 597-604 - [c116]Michael P. Wellman, Achintya Prakash:
Empirical Game-Theoretic Analysis of an Adaptive Cyber-Defense Scenario (Preliminary Report). GameSec 2014: 43-58 - [c115]George Cybenko, Sushil Jajodia, Michael P. Wellman, Peng Liu:
Adversarial and Uncertain Reasoning for Adaptive Cyber Defense: Building the Scientific Foundation. ICISS 2014: 1-8 - [c114]Travis Martin, Grant Schoenebeck, Michael P. Wellman:
Characterizing strategic cascades on networks. EC 2014: 113-130 - [c113]Ben-Alexander Cassell, Michael P. Wellman:
Database Modeling of Empirical Games. DSMM 2014: 6:1-6:6 - [i29]Yagil Engel, Michael P. Wellman:
Multiattribute Auctions Based on Generalized Additive Independence. CoRR abs/1401.3844 (2014) - 2013
- [c112]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 - [c111]Brandon A. Mayer, Eric Sodomka, Amy Greenwald, Michael P. Wellman:
Accounting for price dependencies in simultaneous sealed-bid auctions. EC 2013: 679-696 - [c110]Elaine Wah, Michael P. Wellman:
Latency arbitrage, market fragmentation, and efficiency: a two-market model. EC 2013: 855-872 - [i28]David M. Pennock, Michael P. Wellman:
Compact Securities Markets for Pareto Optimal Reallocation of Risk. CoRR abs/1301.3886 (2013) - [i27]David V. Pynadath, Michael P. Wellman:
Probabilistic State-Dependent Grammars for Plan Recognition. CoRR abs/1301.3888 (2013) - [i26]David M. Pennock, Michael P. Wellman:
Graphical Representations of Consensus Belief. CoRR abs/1301.6732 (2013) - [i25]Chao-Lin Liu, Michael P. Wellman:
Incremental Tradeoff Resolution in Qualitative Probabilistic Networks. CoRR abs/1301.7395 (2013) - [i24]Chao-Lin Liu, Michael P. Wellman:
Using Qualitative Relationships for Bounding Probability Distributions. CoRR abs/1301.7396 (2013) - [i23]David M. Pennock, Michael P. Wellman:
Representing Aggregate Belief through the Competitive Equilibrium of a Securities Market. CoRR abs/1302.1564 (2013) - [i22]David M. Pennock, Michael P. Wellman:
Toward a Market Model for Bayesian Inference. CoRR abs/1302.3593 (2013) - [i21]Peter R. Wurman, Michael P. Wellman:
Optimal Factory Scheduling using Stochastic Dominance A*. CoRR abs/1302.3611 (2013) - [i20]David V. Pynadath, Michael P. Wellman:
Accounting for Context in Plan Recognition, with Application to Traffic Monitoring. CoRR abs/1302.4980 (2013) - [i19]Michael P. Wellman, Matthew Ford, Kenneth Larson:
Path Planning under Time-Dependent Uncertainty. CoRR abs/1302.4987 (2013) - [i18]Marcus J. Huber, Edmund H. Durfee, Michael P. Wellman:
The Automated Mapping of Plans for Plan Recognition. CoRR abs/1302.6821 (2013) - [i17]Michael P. Wellman, Chao-Lin Liu:
State-space Abstraction for Anytime Evaluation of Probabilistic Networks. CoRR abs/1302.6850 (2013) - [i16]Michael P. Wellman:
Exploiting Functional Dependencies in Qualitative Probabilistic Reasoning. CoRR abs/1304.1081 (2013) - [i15]Michael P. Wellman, David Heckerman:
The Role of Calculi in Uncertain Inference Systems. CoRR abs/1304.2747 (2013) - [i14]Michael P. Wellman:
Qualitative Probabilistic Networks for Planning Under Uncertainty. CoRR abs/1304.3115 (2013) - [i13]Bruce D'Ambrosio, Didier Dubois, Philippe Smets, Michael P. Wellman:
Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence (1992). CoRR abs/1304.3852 (2013) - [i12]Michael P. Wellman, Tae Hyung Kim, Quang Duong:
Analyzing Incentives for Protocol Compliance in Complex Domains: A Case Study of Introduction-Based Routing. CoRR abs/1306.0388 (2013) - [i11]Travis Martin, Grant Schoenebeck, Michael P. Wellman:
Characterizing Strategic Cascades on Networks. CoRR abs/1310.2561 (2013) - 2012
- [j60]Yevgeniy Vorobeychik, Daniel M. Reeves, Michael P. Wellman:
Constrained automated mechanism design for infinite games of incomplete information. Auton. Agents Multi Agent Syst. 25(2): 313-351 (2012) - [j59]Ben-Alexander Cassell, Michael P. Wellman:
Asset pricing under ambiguous information: an empirical game-theoretic analysis. Comput. Math. Organ. Theory 18(4): 445-462 (2012) - [c109]Quang Duong, Michael P. Wellman, Satinder Singh, Michael J. Kearns:
Learning and predicting dynamic networked behavior with graphical multiagent models. AAMAS 2012: 441-448 - [c108]Bryce Wiedenbeck, Michael P. Wellman:
Scaling simulation-based game analysis through deviation-preserving reduction. AAMAS 2012: 931-938 - [c107]Michael P. Wellman, Bryce Wiedenbeck:
An empirical game-theoretic analysis of credit network formation. Allerton Conference 2012: 386-393 - [c106]Ben-Alexander Cassell, Michael P. Wellman:
EGTAOnline: An Experiment Manager for Simulation-Based Game Studies. MABS 2012: 85-100 - [c105]Michael P. Wellman, Eric Sodomka, Amy Greenwald:
Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions. UAI 2012: 893-902 - [c104]Pranav Dandekar, Ashish Goel, Michael P. Wellman, Bryce Wiedenbeck:
Strategic formation of credit networks. WWW 2012: 559-568 - [i10]Michael P. Wellman, Lu Hong, Scott E. Page:
The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information. CoRR abs/1202.3768 (2012) - [i9]Quang Duong, Michael P. Wellman, Satinder Singh:
Knowledge Combination in Graphical Multiagent Model. CoRR abs/1206.3248 (2012) - [i8]Yevgeniy Vorobeychik, Daniel M. Reeves, Michael P. Wellman:
Constrained Automated Mechanism Design for Infinite Games of Incomplete Information. CoRR abs/1206.5288 (2012) - [i7]Anna Osepayshvili, Michael P. Wellman, Daniel M. Reeves, Jeffrey K. MacKie-Mason:
Self-Confirming Price Prediction for Bidding in Simultaneous Ascending Auctions. CoRR abs/1207.1400 (2012) - [i6]Daniel M. Reeves, Michael P. Wellman:
Computing Best-Response Strategies in Infinite Games of Incomplete Information. CoRR abs/1207.4171 (2012) - [i5]Michael P. Wellman, Eric Sodomka, Amy Greenwald:
Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions. CoRR abs/1210.4915 (2012) - 2011
- [b3]Michael P. Wellman:
Trading Agents. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2011 - [c103]Quang Duong, Michael P. Wellman, Satinder Singh:
Modeling Information Diffusion in Networks with Unobserved Links. SocialCom/PASSAT 2011: 362-369 - [c102]Ben-Alexander Cassell, Michael P. Wellman:
Agent-based analysis of asset pricing under ambiguous information. SpringSim (ADS) 2011: 21-28 - [c101]Gregory Frazier, Quang Duong, Michael P. Wellman, Edward Petersen:
Incentivizing Responsible Networking via Introduction-Based Routing. TRUST 2011: 277-293 - [c100]Michael P. Wellman, Lu Hong, Scott E. Page:
The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information. UAI 2011: 727-735 - [i4]William E. Walsh, Michael P. Wellman:
Decentralized Supply Chain Formation: A Market Protocol and Competitive Equilibrium Analysis. CoRR abs/1107.0021 (2011) - [i3]Kevin M. Lochner, Daniel M. Reeves, Yevgeniy Vorobeychik, Michael P. Wellman:
Price Prediction in a Trading Agent Competition. CoRR abs/1107.0034 (2011) - 2010
- [j58]Clint R. Bidlack, Michael P. Wellman:
Exceptional Data Quality using Intelligent Matching and Retrieval. AI Mag. 31(1): 65-73 (2010) - [j57]