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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
- 2025
[j78]Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael P. Wellman, Yevgeniy Vorobeychik:
A game-theoretic approach for hierarchical epidemic control. Auton. Agents Multi Agent Syst. 39(1): 14 (2025)- [j77]Michael P. Wellman
, Karl Tuyls, Amy Greenwald:
Empirical Game Theoretic Analysis: A Survey. J. Artif. Intell. Res. 82: 1017-1076 (2025) - [i46]Christine Konicki, Mithun Chakraborty, Michael P. Wellman:
Policy Abstraction and Nash Refinement in Tree-Exploiting PSRO. CoRR abs/2502.02901 (2025) - [i45]Madelyn Gatchel, Michael P. Wellman:
Learning Bayesian Game Families, with Application to Mechanism Design. CoRR abs/2502.14078 (2025) - [i44]Lewis Hammond, Alan Chan, Jesse Clifton, Jason Hoelscher-Obermaier, Akbir Khan, Euan McLean, Chandler Smith, Wolfram Barfuss, Jakob N. Foerster, Tomas Gavenciak, The Anh Han, Edward Hughes, Vojtech Kovarík, Jan Kulveit, Joel Z. Leibo, Caspar Oesterheld, Christian Schröder de Witt, Nisarg Shah, Michael P. Wellman, Paolo Bova, Theodor Cimpeanu, Carson Ezell, Quentin Feuillade-Montixi, Matija Franklin, Esben Kran, Igor Krawczuk, Max Lamparth, Niklas Lauffer, Alexander Meinke, Sumeet Motwani, Anka Reuel, Vincent Conitzer, Michael Dennis, Iason Gabriel, Adam Gleave, Gillian K. Hadfield, Nika Haghtalab, Atoosa Kasirzadeh, Sébastien Krier, Kate Larson, Joel Lehman, David C. Parkes, Georgios Piliouras, Iyad Rahwan:
Multi-Agent Risks from Advanced AI. CoRR abs/2502.14143 (2025) - 2024
- [j76]Michael P. Wellman, Katherine Mayo:
Navigating in a space of game views. Auton. Agents Multi Agent Syst. 38(2): 31 (2024) - [j75]Max Olan Smith, Michael P. Wellman:
Co-Learning Empirical Games & World Models. RLJ 1: 1-15 (2024) - [c168]Yongzhao Wang, Michael P. Wellman:
Generalized Response Objectives for Strategy Exploration in Empirical Game-Theoretic Analysis. AAMAS 2024: 1892-1900 - [c167]Chris Mascioli, Anri Gu, Yongzhao Wang, Mithun Chakraborty, Michael P. Wellman:
A Financial Market Simulation Environment for Trading Agents Using Deep Reinforcement Learning. ICAIF 2024: 117-125 - [c166]Anri Gu, Yongzhao Wang, Chris Mascioli, Mithun Chakraborty, Rahul Savani, Theodore L. Turocy, Michael P. Wellman:
The Effect of Liquidity on the Spoofability of Financial Markets. ICAIF 2024: 239-247 - [c165]Yongzhao Wang, Rahul Savani, Anri Gu, Chris Mascioli, Theodore L. Turocy, Michael P. Wellman:
Market Making with Learned Beta Policies. ICAIF 2024: 643-651 - [c164]Zun Li, Michael P. Wellman:
A Meta-Game Evaluation Framework for Deep Multiagent Reinforcement Learning. IJCAI 2024: 148-156 - [c163]Katherine Mayo, Nicholas Grabill, Michael P. Wellman:
Fraud Risk Mitigation in Real-Time Payments: A Strategic Agent-Based Analysis. IJCAI 2024: 157-165 - [i43]Michael P. Wellman, Karl Tuyls, Amy Greenwald:
Empirical Game-Theoretic Analysis: A Survey. CoRR abs/2403.04018 (2024) - [i42]Zun Li, Michael P. Wellman:
A Meta-Game Evaluation Framework for Deep Multiagent Reinforcement Learning. CoRR abs/2405.00243 (2024) - 2023
- [j74]Max Olan Smith, Thomas W. Anthony, Michael P. Wellman:
Learning to play against any mixture of opponents. Frontiers Artif. Intell. 6 (2023) - [j73]Max Olan Smith, Thomas W. Anthony, Michael P. Wellman:
Strategic Knowledge Transfer. J. Mach. Learn. Res. 24: 233:1-233:96 (2023) - [c162]Yongzhao Wang, Michael P. Wellman:
Empirical Game-Theoretic Analysis for Mean Field Games. AAMAS 2023: 1025-1033 - [c161]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 - [c160]Yongzhao Wang, Michael P. Wellman:
Regularization for Strategy Exploration in Empirical Game-Theoretic Analysis. AAMAS 2023: 2484-2486 - [c159]Yongzhao Wang, Michael P. Wellman:
Game Model Learning for Mean Field Games. AAMAS 2023: 2905-2907 - [c158]Megan Shearer, Gabriel Rauterberg, Michael P. Wellman:
Learning to Manipulate a Financial Benchmark. ICAIF 2023: 592-600 - [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, Gary 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, Gary 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 Hong 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 Hong 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 Hong 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, ISBN 978-3-031-00426-1 - [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]Eric Horvitz, Lise Getoor, Carlos Guestrin, James A. Hendler, Joseph A. Konstan, Devika Subramanian, Michael P. Wellman, Henry A. Kautz:
AI Theory and Practice: A Discussion on Hard Challenges and Opportunities Ahead. AI Mag. 31(3): 103-114 (2010) - [j56]Quang Duong, Kristen LeFevre, Michael P. Wellman:
Strategic Modeling of Information Sharing among Data Privacy Attackers. Informatica (Slovenia) 34(2): 151-158 (2010) - [j55]Yagil Engel, Michael P. Wellman:
Multiattribute Auctions Based on Generalized Additive Independence. J. Artif. Intell. Res. 37: 479-525 (2010) - [c99]Patrick R. Jordan, Michael P. Wellman:
Algorithms for Finding Approximate Formations in Games. AAAI 2010: 798-804 - [c98]Patrick R. Jordan, L. Julian Schvartzman, Michael P. Wellman:
Strategy exploration in empirical games. AAMAS 2010: 1131-1138 - [c97]Quang Duong, Michael P. Wellman, Satinder Singh, Yevgeniy Vorobeychik:
History-dependent graphical multiagent models. AAMAS 2010: 1215-1222 - [c96]Ben-Alexander Cassell, Michael P. Wellman:
Agent-based analysis of asset pricing under ambiguous information. AAMAS 2010: 1493-1494 - [c95]Vinay K. Chaudhri, Bert Bredeweg, Richard Fikes, Sheila A. McIlraith, Michael P. Wellman:
A Categorization of KR&R Methods for Requirement Analysis of a Query Answering Knowledge Base. FOIS 2010: 158-171 - [c94]Patrick R. Jordan, Michael P. Wellman, Guha Balakrishnan:
Strategy and mechanism lessons from the first ad auctions trading agent competition. EC 2010: 287-296
2000 – 2009
- 2009
- [j54]Christopher Kiekintveld, Jason Miller, Patrick R. Jordan, Lee F. Callender, Michael P. Wellman:
Forecasting market prices in a supply chain game. Electron. Commer. Res. Appl. 8(2): 63-77 (2009) - [c93]Patrick R. Jordan, Michael P. Wellman:
Designing an Ad Auctions Game for the Trading Agent Competition. AMEC/TADA 2009: 147-162 - [c92]L. Julian Schvartzman, Michael P. Wellman:
Learning Improved Entertainment Trading Strategies for the TAC Travel Game. AMEC/TADA 2009: 195-210 - [c91]Kevin M. Lochner, Michael P. Wellman:
Information Feedback and Efficiency in Multiattribute Double Auctions. AMMA 2009: 26-39 - [c90]L. Julian Schvartzman, Michael P. Wellman:
Stronger CDA strategies through empirical game-theoretic analysis and reinforcement learning. AAMAS (1) 2009: 249-256 - [c89]Patrick R. Jordan, Michael P. Wellman:
Generalization risk minimization in empirical game models. AAMAS (1) 2009: 553-560 - [c88]Azzurra Ragone, Tommaso Di Noia, Francesco M. Donini, Eugenio Di Sciascio, Michael P. Wellman:
Computing Utility from Weighted Description Logic Preference Formulas. DALT 2009: 158-173 - [c87]Quang Duong, Yevgeniy Vorobeychik, Satinder Singh, Michael P. Wellman:
Learning Graphical Game Models. IJCAI 2009: 116-121 - [c86]Azzurra Ragone, Tommaso Di Noia, Francesco M. Donini, Eugenio Di Sciascio, Michael P. Wellman:
Weighted Description Logics Preference Formulas for Multiattribute Negotiation. SUM 2009: 193-205 - [c85]Yevgeniy Vorobeychik, Michael P. Wellman:
Strategic Analysis with Simulation-based Games. WSC 2009: 359-372 - 2008
- [j53]Yagil Engel, Michael P. Wellman:
CUI Networks: A Graphical Representation for Conditional Utility Independence. J. Artif. Intell. Res. 31: 83-112 (2008) - [j52]Michael P. Wellman, Amy Greenwald, Peter Stone:
Book announcement: autonomous bidding agents. SIGecom Exch. 7(2) (2008) - [c84]Yevgeniy Vorobeychik, Michael P. Wellman:
Stochastic search methods for nash equilibrium approximation in simulation-based games. AAMAS (2) 2008: 1055-1062 - [c83]Patrick R. Jordan, Yevgeniy Vorobeychik, Michael P. Wellman:
Searching for approximate equilibria in empirical games. AAMAS (2) 2008: 1063-1070 - [c82]Christopher Kiekintveld, Michael P. Wellman:
Selecting strategies using empirical game models: an experimental analysis of meta-strategies. AAMAS (2) 2008: 1095-1101 - [c81]Quang Duong, Michael P. Wellman, Satinder Singh:
Knowledge Combination in Graphical Multiagent Models. UAI 2008: 153-160 - 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 - [j51]Rakesh V. Vohra, Michael P. Wellman:
Foundations of multi-agent learning: Introduction to the special issue. Artif. Intell. 171(7): 363-364 (2007) - [j50]Sarabjot Singh Anand, Daniel Bahls, Catherina Burghart, Mark H. Burstein, Huajun Chen, John Collins, Thomas G. Dietterich, Jon Doyle, Chris Drummond, William Elazmeh, Christopher W. Geib, Judy Goldsmith, Hans W. Guesgen, Jim Hendler, Dietmar Jannach, Nathalie Japkowicz, Ulrich Junker, Gal A. Kaminka, Alfred Kobsa, Jérôme Lang, David B. Leake, Lundy Lewis, Gerard Ligozat, Sofus A. Macskassy, Drew V. McDermott, Ted Metzler, Bamshad Mobasher, Ullas Nambiar, Zaiqing Nie, Klas Orsvärn, Barry O'Sullivan, David V. Pynadath, Jochen Renz, Rita V. Rodríguez, Thomas Roth-Berghofer, Stefan Schulz, Rudi Studer, Yimin Wang, Michael P. Wellman:
AAAI-07 Workshop Reports. AI Mag. 28(4): 119-128 (2007) - [j49]Yevgeniy Vorobeychik, Michael P. Wellman, Satinder Singh:
Learning payoff functions in infinite games. Mach. Learn. 67(1-2): 145-168 (2007) - [c80]Vishal Soni, Satinder Singh, Michael P. Wellman:
Constraint satisfaction algorithms for graphical games. AAMAS 2007: 67 - [c79]Patrick R. Jordan, Christopher Kiekintveld, Michael P. Wellman:
Empirical game-theoretic analysis of the TAC Supply Chain game. AAMAS 2007: 193 - [c78]Christopher Kiekintveld, Jason Miller, Patrick R. Jordan, Michael P. Wellman:
Forecasting market prices in a supply chain game. AAMAS 2007: 234 - [c77]Shih-Fen Cheng, Michael P. Wellman:
Iterated Weaker-than-Weak Dominance. IJCAI 2007: 1233-1238 - [c76]Yagil Engel, Michael P. Wellman:
Generalized value decomposition and structured multiattribute auctions. EC 2007: 227-236 - [c75]Yevgeniy Vorobeychik, Daniel M. Reeves, Michael P. Wellman:
Constrained Automated Mechanism Design for Infinite Games of Incomplete Information. UAI 2007: 400-407 - 2006
- [c74]Yagil Engel, Michael P. Wellman:
CUI Networks: A Graphical Representation for Conditional Utility Independence. AAAI 2006: 1137-1142 - [c73]Michael P. Wellman:
Methods for Empirical Game-Theoretic Analysis. AAAI 2006: 1552-1556 - [c72]Patrick R. Jordan, Christopher Kiekintveld, Jason Miller, Michael P. Wellman:
Market Efficiency, Sales Competition, and the Bullwhip Effect in the TAC SCM Tournaments. TADA/AMEC 2006: 62-74 - [c71]Yagil Engel, Michael P. Wellman, Kevin M. Lochner:
Bid expressiveness and clearing algorithms in multiattribute double auctions. EC 2006: 110-119 - [c70]Christopher Kiekintveld, Jason Miller, Patrick R. Jordan, Michael P. Wellman:
Controlling a supply chain agent using value-based decomposition. EC 2006: 208-217 - [c69]Yevgeniy Vorobeychik, Christopher Kiekintveld, Michael P. Wellman:
Empirical mechanism design: methods, with application to a supply-chain scenario. EC 2006: 306-315 - [e4]Hideyuki Nakashima, Michael P. Wellman, Gerhard Weiss, Peter Stone:
5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, May 8-12, 2006. ACM 2006, ISBN 1-59593-303-4 [contents] - 2005
- [j48]Michael P. Wellman, Joshua Estelle, Satinder Singh, Yevgeniy Vorobeychik, Christopher Kiekintveld, Vishal Soni:
Strategic Interactions in a Supply Chain Game. Comput. Intell. 21(1): 1-26 (2005) - [j47]David M. Pennock, Michael P. Wellman:
Graphical Models for Groups: Belief Aggregation and Risk Sharing. Decis. Anal. 2(3): 148-164 (2005) - [j46]Daniel M. Reeves, Michael P. Wellman, Jeffrey K. MacKie-Mason, Anna Osepayshvili:
Exploring bidding strategies for market-based scheduling. Decis. Support Syst. 39(1): 67-85 (2005) - [j45]Lance Fortnow, Joe Kilian, David M. Pennock, Michael P. Wellman:
Betting Boolean-style: a framework for trading in securities based on logical formulas. Decis. Support Syst. 39(1): 87-104 (2005) - [j44]Shih-Fen Cheng, Evan Leung, Kevin M. Lochner, Kevin O'Malley, Daniel M. Reeves, L. Julian Schvartzman, Michael P. Wellman:
Walverine: a Walrasian trading agent. Decis. Support Syst. 39(2): 169-184 (2005) - [c68]Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, Shih-Fen Cheng, Rahul Suri:
Approximate Strategic Reasoning through Hierarchical Reduction of Large Symmetric Games. AAAI 2005: 502-508 - [c67]L. Julian Schvartzman, Michael P. Wellman:
Market-Based Allocation with Indivisible Bids. AMEC@AAMAS/TADA@IJCAI 2005: 57-70 - [c66]Christopher Kiekintveld, Yevgeniy Vorobeychik, Michael P. Wellman:
An Analysis of the 2004 Supply Chain Management Trading Agent Competition. AMEC@AAMAS/TADA@IJCAI 2005: 99-112 - [c65]Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, Rahul Suri:
Searching for Walverine 2005. AMEC@AAMAS/TADA@IJCAI 2005: 157-170 - [c64]Yevgeniy Vorobeychik, Michael P. Wellman, Satinder Singh:
Learning Payoff Functions in Infinite Games. IJCAI 2005: 977-982 - [c63]Anna Osepayshvili, Michael P. Wellman, Daniel M. Reeves, Jeffrey K. MacKie-Mason:
Self-Confirming Price Prediction for Bidding in Simultaneous Ascending Auctions. UAI 2005: 441-449 - [i2]Anna Osepayshvili, Michael P. Wellman, Daniel M. Reeves, Jeffrey K. MacKie-Mason:
Self-Confirming Price Prediction for Bidding in Simultaneous Ascending Auctions. Computing and Markets 2005 - 2004
- [j43]Chao-Lin Liu, Michael P. Wellman:
Bounding probabilistic relationships in Bayesian networks using qualitative influences: methods and applications. Int. J. Approx. Reason. 36(1): 31-73 (2004) - [j42]Michael P. Wellman, John Riedl:
Introduction to the Special Issue: Matching Buyers and Sellers for e-Commerce. Int. J. Electron. Commer. 8(4): 7-8 (2004) - [j41]Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, Yevgeniy Vorobeychik:
Price Prediction in a Trading Agent Competition. J. Artif. Intell. Res. 21: 19-36 (2004) - [j40]Christopher Kiekintveld, Michael P. Wellman, Satinder Singh, Vishal Soni:
Value-driven procurement in the TAC supply chain game. SIGecom Exch. 4(3): 9-18 (2004) - [c62]Yevgeniy Vorobeychik, Michael P. Wellman, Satinder Singh:
Learning Payoff Functions in Infinite Games. AAAI Technical Report (2) 2004: 60-65 - [c61]Jeffrey K. MacKie-Mason, Anna Osepayshvili, Daniel M. Reeves, Michael P. Wellman:
Price Prediction Strategies for Market-Based Scheduling. ICAPS 2004: 244-252 - [c60]Christopher Kiekintveld, Michael P. Wellman, Satinder Singh, Joshua Estelle, Yevgeniy Vorobeychik, Vishal Soni, Matthew R. Rudary:
Distributed Feedback Control for Decision Making on Supply Chains. ICAPS 2004: 384-392 - [c59]Kevin M. Lochner, Michael P. Wellman:
Rule-Based Specification of Auction Mechanisms. AAMAS 2004: 818-825 - [c58]Joshua Estelle, Yevgeniy Vorobeychik, Michael P. Wellman, Satinder Singh, Christopher Kiekintveld, Vishal Soni:
Strategic Interactions in the TAC 2003 Supply Chain Tournament. Computers and Games 2004: 316-331 - [c57]Satinder Singh, Vishal Soni, Michael P. Wellman:
Computing approximate bayes-nash equilibria in tree-games of incomplete information. EC 2004: 81-90 - [c56]Daniel M. Reeves, Michael P. Wellman:
Computing Best-Response Strategies in Infinite Games of Incomplete Information. UAI 2004: 470-478 - [r1]Michael P. Wellman:
Online Marketplaces. The Practical Handbook of Internet Computing 2004 - 2003
- [j39]William E. Walsh, Makoto Yokoo, Katsutoshi Hirayama, Michael P. Wellman:
On market-inspired approaches to propositional satisfiability. Artif. Intell. 144(1-2): 125-156 (2003) - [j38]Michael P. Wellman, Amy Greenwald, Peter Stone, Peter R. Wurman:
The 2001 Trading Agent Competition. Electron. Mark. 13(1): 4-12 (2003) - [j37]Michael P. Wellman, Shih-Fen Cheng, Daniel M. Reeves, Kevin M. Lochner:
Trading Agents Competing: Performance, Progress, and Market Effectiveness. IEEE Intell. Syst. 18(6): 48-53 (2003) - [j36]William E. Walsh, Michael P. Wellman:
Decentralized Supply Chain Formation: A Market Protocol and Competitive Equilibrium Analysis. J. Artif. Intell. Res. 19: 513-567 (2003) - [j35]Junling Hu, Michael P. Wellman:
Nash Q-Learning for General-Sum Stochastic Games. J. Mach. Learn. Res. 4: 1039-1069 (2003) - [j34]Michael P. Wellman, Daniel A. Menascé, Peter R. Wurman:
Letter from the new chair. SIGecom Exch. 4(2) (2003) - [c55]Shih-Fen Cheng, Evan Leung, Kevin M. Lochner, Kevin O'Malley, Daniel M. Reeves, L. Julian Schvartzman, Michael P. Wellman:
Walverine: a Walrasian trading agent. AAMAS 2003: 465-472 - [c54]Shih-Fen Cheng, Michael P. Wellman, Dennis G. Perry:
Market-Based Resource Allocation for Information-Collection Scenarios. MAMUS 2003: 33-47 - [c53]Michael P. Wellman, Jeffrey K. MacKie-Mason, Daniel M. Reeves, Sowmya Swaminathan:
Exploring bidding strategies for market-based scheduling. EC 2003: 115-124 - [c52]Lance Fortnow, Joe Kilian, David M. Pennock, Michael P. Wellman:
Betting boolean-style: a framework for trading in securities based on logical formulas. EC 2003: 144-155 - [c51]Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner:
Price prediction in a trading agent competition (extended abstract). EC 2003: 216-217 - 2002
- [j33]Peter R. Wurman, Michael P. Wellman, William E. Walsh:
Specifying Rules for Electronic Auctions. AI Mag. 23(3): 15-24 (2002) - [j32]Daniel M. Reeves, Michael P. Wellman, Benjamin N. Grosof:
Automated Negotiation from Declarative Contract Descriptions. Comput. Intell. 18(4): 482-500 (2002) - [j31]Chao-Lin Liu, Michael P. Wellman:
Evaluation of Bayesian networks with flexible state-space abstraction methods. Int. J. Approx. Reason. 30(1): 1-39 (2002) - [c50]Michael P. Wellman, Amy Greenwald, Peter Stone, Peter R. Wurman:
The 2001 Trading Agent Competition. AAAI/IAAI 2002: 935-942 - 2001
- [j30]Junling Hu, Michael P. Wellman:
Learning about other agents in a dynamic multiagent system. Cogn. Syst. Res. 2(1): 67-79 (2001) - [j29]Junling Hu, Michael P. Wellman:
Erratum to "Learning about other agents in a dynamic multiagent system": [Cognitive Systems Research 2 (2001) 67-79]⋆. Cogn. Syst. Res. 2(3): 233 (2001) - [j28]Michael P. Wellman, William E. Walsh, Peter R. Wurman, Jeffrey K. MacKie-Mason:
Auction Protocols for Decentralized Scheduling. Games Econ. Behav. 35(1-2): 271-303 (2001) - [j27]Peter R. Wurman, Michael P. Wellman, William E. Walsh:
A Parametrization of the Auction Design Space. Games Econ. Behav. 35(1-2): 304-338 (2001) - [j26]Michael P. Wellman, Peter R. Wurman, Kevin O'Malley, Roshan Bangera, Shou-De Lin, Daniel M. Reeves, William E. Walsh:
Designing the Market Game for a Trading Agent Competition. IEEE Internet Comput. 5(2): 43-51 (2001) - [c49]Daniel M. Reeves, Michael P. Wellman, Benjamin N. Grosof:
Automated negotiation from declarative contract descriptions. Agents 2001: 51-58 - [c48]William E. Walsh, Makoto Yokoo, Katsutoshi Hirayama, Michael P. Wellman:
On Market-Inspired Approaches to Propositional Satisfiability. IJCAI 2001: 1152-1160 - [e3]Michael P. Wellman, Yoav Shoham:
Proceedings 3rd ACM Conference on Electronic Commerce (EC-2001), Tampa, Florida, USA, October 14-17, 2001. ACM 2001, ISBN 1-58113-387-1 [contents] - 2000
- [c47]William E. Walsh, Michael P. Wellman:
MarketSAT: An Extremely Decentralized (but Really Slow) Algorithm for Propositional Satisfiability. AAAI/IAAI 2000: 303-309 - [c46]Michael P. Wellman, William E. Walsh:
Distributed Quiescence Detection in Multiagent Negotiation. ICMAS 2000: 317-324 - [c45]Junling Hu, Michael P. Wellman:
Experimental Results on Q-Learning for General-Sum Stochastic Games. ICML 2000: 407-414 - [c44]Peter R. Wurman, Michael P. Wellman:
AkBA: a progressive, anonymous-price combinatorial auction. EC 2000: 21-29 - [c43]William E. Walsh, Michael P. Wellman, Fredrik Ygge:
Combinatorial auctions for supply chain formation. EC 2000: 260-269 - [c42]David M. Pennock, Michael P. Wellman:
Compact Securities Markets for Pareto Optimal Reallocation of Risk. UAI 2000: 481-488 - [c41]David V. Pynadath, Michael P. Wellman:
Probabilistic State-Dependent Grammars for Plan Recognition. UAI 2000: 507-514
1990 – 1999
- 1999
- [j25]Steven Minton, Michael P. Wellman:
JAIR at Five. AI Mag. 20(2): 83-91 (1999) - [c40]Michael P. Wellman:
Agents and Electronic Commerce: Mechanisms and Protocols (Abstract). CIA 1999: 243-244 - [c39]William E. Walsh, Michael P. Wellman:
Modeling Supply Chain Formation in Multiagent Systems. Agent Mediated Electronic Commerce (IJCAI Workshop) 1999: 94-101 - [c38]William E. Walsh, Michael P. Wellman:
Efficiency and Equilibrium in Task Allocation Economies with Hierarchical Dependencies. IJCAI 1999: 520-526 - [c37]David M. Pennock, Michael P. Wellman:
Graphical Representations of Consensus Belief. UAI 1999: 531-540 - [e2]Stuart I. Feldman, Michael P. Wellman:
Proceedings of the First ACM Conference on Electronic Commerce (EC-99), Denver, CO, USA, November 3-5, 1999. ACM 1999, ISBN 1-58113-176-3 [contents] - 1998
- [j24]Peter R. Wurman, William E. Walsh, Michael P. Wellman:
Flexible double auctions for electronic commerce: theory and implementation. Decis. Support Syst. 24(1): 17-27 (1998) - [j23]Michael P. Wellman, Junling Hu:
Conjectural Equilibrium in Multiagent Learning. Mach. Learn. 33(2-3): 179-200 (1998) - [j22]David V. Pynadath, Michael P. Wellman:
Generalized Queries on Probabilistic Context-Free Grammars. IEEE Trans. Pattern Anal. Mach. Intell. 20(1): 65-77 (1998) - [j21]Michael P. Wellman, Peter R. Wurman:
Market-aware agents for a multiagent world. Robotics Auton. Syst. 24(3-4): 115-125 (1998) - [c36]Junling Hu, Michael P. Wellman:
Online Learning about Other Agents in a Dynamic Multiagent System. Agents 1998: 239-246 - [c35]Peter R. Wurman, Michael P. Wellman, William E. Walsh:
The Michigan Internet AcutionBot: A Configuarable Auction Server for Human and Software Agents. Agents 1998: 301-308 - [c34]William E. Walsh, Michael P. Wellman, Peter R. Wurman, Jeffrey K. MacKie-Mason:
Some Economics of Market-Based Distributed Scheduling. ICDCS 1998: 612-621 - [c33]William E. Walsh, Michael P. Wellman:
A Market Protocol for Decentralized Task Allocation. ICMAS 1998: 325-332 - [c32]Junling Hu, Michael P. Wellman:
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm. ICML 1998: 242-250 - [c31]Chao-Lin Liu, Michael P. Wellman:
Incremental Tradeoff Resolution in Qualitative Probabilistic Networks. UAI 1998: 338-345 - [c30]Chao-Lin Liu, Michael P. Wellman:
Using Qualitative Relationships for Bounding Probability Distributions. UAI 1998: 346-353 - [c29]Tracy Mullen, Michael P. Wellman:
The Auction Manager: Market Middleware for Large-Scale Electronic Commerce. USENIX Workshop on Electronic Commerce 1998 - 1997
- [j20]Craig Boutilier, Yoav Shoham, Michael P. Wellman:
Economic Principles of Multi-Agent Systems. Artif. Intell. 94(1-2): 1-6 (1997) - [c28]Michael P. Wellman:
Market-Oriented Programming (Abstract). AAAI/IAAI 1997: 774 - [c27]Michael P. Wellman:
Market-Aware Agents for a Multiagent World. MAAMAW 1997: 1 - [c26]David M. Pennock, Michael P. Wellman:
Representing Aggregate Belief through the Competitive Equilibrium of a Securities Market. UAI 1997: 392-400 - 1996
- [j19]Daniel E. Atkins, William P. Birmingham, Edmund H. Durfee, Eric J. Glover, Tracy Mullen, Elke A. Rundensteiner, Elliot Soloway, José M. Vidal, Raven Wallace, Michael P. Wellman:
Toward Inquiry-Based Education Through Interacting Software Agents. Computer 29(5): 69-76 (1996) - [j18]Michael P. Wellman:
The Economic Approach to Artificial Intelligence. ACM Comput. Surv. 28(4es): 14 (1996) - [j17]Chao-Lin Liu, Michael P. Wellman:
On State-Space Abstraction for Anytime Evaluation of Bayesian Networks. SIGART Bull. 7(2): 50-57 (1996) - [c25]David V. Pynadath, Michael P. Wellman:
Generalized Queries on Probabilistic Context-Free Grammars. AAAI/IAAI, Vol. 2 1996: 1285-1290 - [c24]David M. Pennock, Michael P. Wellman:
Toward a Market Model for Bayesian Inference. UAI 1996: 405-413 - [c23]Peter R. Wurman, Michael P. Wellman:
Optimal Factory Scheduling using Stochastic Dominance A*. UAI 1996: 554-563 - 1995
- [j16]Michael P. Wellman:
A computational market model for distributed configuration design. Artif. Intell. Eng. Des. Anal. Manuf. 9(2): 125-133 (1995) - [j15]David Heckerman, E. H. Mamdani, Michael P. Wellman:
Real-World Applications of Bayesian Networks - Introduction. Commun. ACM 38(3): 24-26 (1995) - [j14]David Heckerman, Michael P. Wellman:
Bayesian Networks. Commun. ACM 38(3): 27-30 (1995) - [j13]Michael P. Wellman:
The Economic Approach to Artificial Intelligence. ACM Comput. Surv. 27(3): 360-362 (1995) - [j12]David Heckerman, E. H. Mamdani, Michael P. Wellman:
Editorial: real-world applications of uncertain reasoning. Int. J. Hum. Comput. Stud. 42(6): 573-574 (1995) - [c22]Tracy Mullen, Michael P. Wellman:
Some Issues in the Design of Market-Oriented Agents. ATAL 1995: 283-298 - [c21]Tracy Mullen, Michael P. Wellman:
A Simple Computational Market for Network Information Services. ICMAS 1995: 283-289 - [c20]Michael P. Wellman:
Market-Oriented Programming (Abstract). SBIA 1995: 26-27 - [c19]David V. Pynadath, Michael P. Wellman:
Accounting for Context in Plan Recognition, with Application to Traffic Monitoring. UAI 1995: 472-481 - [c18]Michael P. Wellman, Matthew Ford, Kenneth Larson:
Path Planning under Time-Dependent Uncertainty. UAI 1995: 532-539 - 1994
- [j11]Michael P. Wellman:
Kyburgian Acceptance: A Rejection, Hedged. Comput. Intell. 10: 103-106 (1994) - [c17]Michael P. Wellman:
A Computational Market Model for Distributed Configuration Design. AAAI 1994: 401-407 - [c16]Marcus J. Huber, Edmund H. Durfee, Michael P. Wellman:
The Automated Mapping of Plans for Plan Recognition. AAAI 1994: 1460 - [c15]Michael P. Wellman:
Some Varieties of Qualitative Probability. IPMU 1994: 171-179 - [c14]Marcus J. Huber, Edmund H. Durfee, Michael P. Wellman:
The Automated Mapping of Plans for Plan Recognition. UAI 1994: 344-351 - [c13]Michael P. Wellman, Chao-Lin Liu:
State-Space Abstraction for Anytime Evaluation of Probabilistic Networks. UAI 1994: 567-574 - 1993
- [j10]Michael P. Wellman:
A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems. J. Artif. Intell. Res. 1: 1-23 (1993) - [j9]Michael P. Wellman, Max Henrion:
Explaining 'Explaining Away'. IEEE Trans. Pattern Anal. Mach. Intell. 15(3): 287-292 (1993) - [i1]Michael P. Wellman:
A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems. CoRR cs.AI/9308102 (1993) - 1992
- [j8]Michael P. Wellman:
B. A. Huberman, ed., The Ecology of Computation. Artif. Intell. 52(2): 205-218 (1992) - [j7]Michael P. Wellman:
Whither Qualitative Reasoning? A Response to Sacks and Doyle. Comput. Intell. 8: 277-280 (1992) - [j6]Michael P. Wellman, John S. Breese, Robert P. Goldman:
From knowledge bases to decision models. Knowl. Eng. Rev. 7(1): 35-53 (1992) - [c12]Michael P. Wellman:
A General-Equilibrium Approach to Distributed Transportation Planning. AAAI 1992: 282-289 - [e1]Didier Dubois, Michael P. Wellman:
UAI '92: Proceedings of the Eighth Annual Conference on Uncertainty in Artificial Intelligence, Stanford University, Stanford, CA, USA, July 17-19, 1992. Morgan Kaufmann 1992, ISBN 1-55860-258-5 [contents] - 1991
- [j5]Jon Doyle, Michael P. Wellman:
Impediments to Universal Preference-Based Default Theories. Artif. Intell. 49(1-3): 97-128 (1991) - [c11]Michael P. Wellman, Jon Doyle:
Preferential Semantics for Goals. AAAI 1991: 698-703 - [c10]Jon Doyle, Yoav Shoham, Michael P. Wellman:
A Logic of Relative Desire (Preliminary Report). ISMIS 1991: 16-31 - [c9]Michael P. Wellman, Max Henrion:
Qualitative Intercausal Relations, or Explaining "Explaining Away". KR 1991: 535-546 - [c8]Michael P. Wellman:
Qualitative Simulation with Multivariate Constraints. KR 1991: 547-557 - 1990
- [j4]Michael P. Wellman:
Fundamental Concepts of Qualitative Probabilistic Networks. Artif. Intell. 44(3): 257-303 (1990) - [j3]Michael P. Wellman:
Graphical inference in qualitative probabilistic networks. Networks 20(5): 687-701 (1990) - [c7]Michael P. Wellman:
The STRIPS Assumption for Planning Under Uncertainty. AAAI 1990: 198-203 - [c6]Michael P. Wellman:
Exploiting functional dependencies in qualitative probabilistic reasoning. UAI 1990: 3-16
1980 – 1989
- 1989
- [c5]Jon Doyle, Michael P. Wellman:
Impediments to Universal Preference-Based Default Theories. KR 1989: 94-102 - 1988
- [b1]Michael P. Wellman:
Formulation of tradeoffs in planning under uncertainty. Massachusetts Institute of Technology, Cambridge, MA, USA, 1988 - [j2]Michael P. Wellman:
P. L. Miller, Expert Critiquing Systems: Practice-Based Medical Consultation by Computer. Artif. Intell. 35(2): 273-276 (1988) - [j1]Michael P. Wellman:
The role of calculi in uncertain reasoning. Int. J. Approx. Reason. 2(3): 344-345 (1988) - [c4]Michael P. Wellman, Reid G. Simmons:
Mechanisms for Reasoning about Sets. AAAI 1988: 398-402 - 1987
- [c3]Michael P. Wellman:
Probabilistic Semantics for Qualitative Influences. AAAI 1987: 662-664 - [c2]Michael P. Wellman:
Dominance and Subsumption in Constraint-Posting Planning. IJCAI 1987: 884-890 - 1986
- [c1]Michael P. Wellman:
Qualitativce probabilistic networks for planning under uncertainty. UAI 1986: 197-208
Coauthor Index
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last updated on 2025-04-08 20:53 CEST by the dblp team
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