Building Action Sets in a Deep Reinforcement Learner

Y Wang, A Sinha, S CH-Wang, and MP Wellman 20th IEEE International Conference on Machine Learning and Applications (ICMLA), December 2021 (forthcoming). Abstract In many policy-learning applications, the agent may execute a set of actions…

Designing a Combinatorial Financial Options Market

X Wang, DM Pennock, NR Devanur, DM Rothschild, B Tao, and MP Wellman 22nd ACM Conference on Economics and Computation (EC), pages 864-883, July 2021. Abstract Financial options are contracts that specify the right to buy or sell an underlying…

Spoofing the Limit Order Book: A Strategic Agent-Based Analysis

X Wang, C Hoang, Y Vorobeychik, and MP Wellman Games 2021 12(2) 46, May 2021. Abstract We present an agent-based model of manipulating prices in financial markets through spoofing: submitting spurious orders to mislead traders who learn from…

Log-time Prediction Markets for Interval Securities

M Dudík, X Wang, D Pennock, and D Rothschild 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 465-473, May 2021. Abstract We design a prediction market to recover a complete and fully general probability…

A Strategic Analysis of Portfolio Compression

K Mayo and MP Wellman 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Extended Abstract, pages 1599-1601, May 2021. Abstract Portfolio compression, the netting of cycles in a financial network, is employed…

Evolution Strategies for Approximate Solution of Bayesian Games

Z Li and MP Wellman 35th AAAI Conference on Artificial Intelligence, pages 5531-5540, Feb 2021. Abstract We address the problem of solving complex Bayesian games, characterized by high-dimensional type and action spaces, many (> 2) players,…

Iterative Empirical Game Solving via Single Policy Best Response

M Smith, T Anthony, and MP Wellman 9th International Conference on Learning Representations (ICLR), Spotlight Presentation, May 2021. Abstract Policy-Space Response Oracles (PSRO) is a general algorithmic framework for learning policies in…