Michael Wellman

Michael Wellman

University of Michigan

H-index: 73

North America-United States

About Michael Wellman

Michael Wellman, With an exceptional h-index of 73 and a recent h-index of 27 (since 2020), a distinguished researcher at University of Michigan, specializes in the field of Artificial Intelligence, Computational Finance, Computational Game Theory.

His recent articles reflect a diverse array of research interests and contributions to the field:

Generalized Response Objectives for Strategy Exploration in Empirical Game-Theoretic Analysis

A Meta-Game Evaluation Framework for Deep Multiagent Reinforcement Learning

Empirical Game-Theoretic Analysis: A Survey

Combining tree-search, generative models, and nash bargaining concepts in game-theoretic reinforcement learning

Learning to Manipulate a Financial Benchmark

Strategic knowledge transfer

Learning to play against any mixture of opponents

Flagging Payments for Fraud Detection: A Strategic Agent-Based Model

Michael Wellman Information

University

Position

Professor of Computer Science & Engineering

Citations(all)

22257

Citations(since 2020)

5521

Cited By

19196

hIndex(all)

73

hIndex(since 2020)

27

i10Index(all)

202

i10Index(since 2020)

78

Email

University Profile Page

University of Michigan

Google Scholar

View Google Scholar Profile

Michael Wellman Skills & Research Interests

Artificial Intelligence

Computational Finance

Computational Game Theory

Top articles of Michael Wellman

Title

Journal

Author(s)

Publication Date

Generalized Response Objectives for Strategy Exploration in Empirical Game-Theoretic Analysis

Yongzhao Wang

Michael P Wellman

2024/5/6

A Meta-Game Evaluation Framework for Deep Multiagent Reinforcement Learning

arXiv preprint arXiv:2405.00243

Zun Li

Michael P Wellman

2024/4/30

Empirical Game-Theoretic Analysis: A Survey

arXiv preprint arXiv:2403.04018

Michael P Wellman

Karl Tuyls

Amy Greenwald

2024/3/6

Combining tree-search, generative models, and nash bargaining concepts in game-theoretic reinforcement learning

arXiv preprint arXiv:2302.00797

Zun Li

Marc Lanctot

Kevin R McKee

Luke Marris

Ian Gemp

...

2023/2/1

Learning to Manipulate a Financial Benchmark

Megan Shearer

Gabriel Rauterberg

Michael P Wellman

2023/11/27

Strategic knowledge transfer

Journal of Machine Learning Research

Max Olan Smith

Thomas Anthony

Michael P Wellman

2023

Learning to play against any mixture of opponents

Frontiers in Artificial Intelligence

Max Olan Smith

Thomas Anthony

Michael P Wellman

2023/7/20

Flagging Payments for Fraud Detection: A Strategic Agent-Based Model

Katherine Mayo

Shaily Fozdar

Michael P Wellman

2023

Game Model Learning for Mean Field Games

Yongzhao Wang

Michael P Wellman

2023/5/30

Co-Learning Empirical Games and World Models

arXiv preprint arXiv:2305.14223

Max Olan Smith

Michael P Wellman

2023/5/23

Regularization for Strategy Exploration in Empirical Game-Theoretic Analysis

arXiv preprint arXiv:2302.04928

Yongzhao Wang

Michael P Wellman

2023/2/9

Exploiting extensive-form structure in empirical game-theoretic analysis

Christine Konicki

Mithun Chakraborty

Michael P Wellman

2022/12/9

Spoofing the limit order book: A strategic agent-based analysis

Games

Xintong Wang

Christopher Hoang

Yevgeniy Vorobeychik

Michael P Wellman

2021/5/24

Stability effects of arbitrage in exchange traded funds: An agent-based model

Megan Shearer

David Byrd

Tucker Hybinette Balch

Michael P Wellman

2021/11/3

Evaluating strategy exploration in empirical game-theoretic analysis

arXiv preprint arXiv:2105.10423

Yongzhao Wang

Qiurui Ma

Michael P Wellman

2021/5/21

An agent-based model of strategic adoption of real-time payments

Katherine Mayo

Shaily Fozdar

Michael P Wellman

2021/11/3

Evolution strategies for approximate solution of Bayesian games

Thirty-Fifth AAAI Conference on Artificial Intelligence

Zun Li

Michael P Wellman

2021/5/18

A strategic analysis of portfolio compression

Katherine Mayo

Michael P Wellman

2021/11/3

A game-theoretic approach for hierarchical policy-making

CoRR, abs/2102.10646

Feiran Jia

Aditya Mate

Zun Li

Shahin Jabbari

Mithun Chakraborty

...

2021/2/21

Designing a Combinatorial Financial Options Market

Xintong Wang

David M Pennock

Nikhil R Devanur

David M Rothschild

Biaoshuai Tao

...

2021/7/18

See List of Professors in Michael Wellman University(University of Michigan)

Co-Authors

H-index: 77
Satinder Singh

Satinder Singh

University of Michigan-Dearborn

H-index: 73
David C. Parkes

David C. Parkes

Harvard University

H-index: 62
Edmund Durfee

Edmund Durfee

University of Michigan

H-index: 55
David M Pennock

David M Pennock

Rutgers, The State University of New Jersey

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