Mason Wright

Economic reasoning from simulation-based game models

MP Wellman Œconomia, 10(2):257–278, 2020. Abstract Simulation modeling in economics has historically been viewed as an alternative to mainstream analytic technique, and as such has generally and intentionally avoided the focus on rational…
Mason Wright

Empirical game-theoretic methods for adaptive cyber-defense

MP Wellman, TH Nguyen, and M Wright in S Jajodia et al. (Eds.): Adversarial and Uncertain Reasoning for Adaptive Cyber Defense, LNCS 11830, pages 112–128, 2019. Abstract Game-theoretic applications in cyber-security are often restricted…
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interview with Grainstone Lee

I spoke with Simon Grainger recently for his firm's "Views from Academia" series. The interview is based on presentations I've made recently on "Game Playing meets Game Theory", discussing the connection between game-theoretic reasoning and…
Mason Wright

Structure learning for approximate solution of many-player games

Z Li and MP Wellman 34th AAAI Conference on Artificial Intelligence, pages 2119-2127, Feb 2020. Abstract Games with many players are difficult to solve or even specify without adopting structural assumptions that enable representation in…
Mason Wright

Cap-and-trade emissions regulation: A strategic analysis

F Cheng , Y Engel, and MP Wellman Proceedings of the 28th International Joint Conference on Artificial Intelligence, pages 187–193, August 2019. Abstract Cap-and-trade schemes are designed to achieve target levels of regulated emissions…
Mason Wright

Probably almost-stable strategy profiles in simulation-based games

M Wright and MP Wellman AAMAS-19 Workshop on Games, Agents and Incentives, May 2019. Abstract Empirical studies of strategic settings commonly model player interactions under supposed game-theoretic equilibrium behavior, to predict what…
Mason Wright

Iterated Deep Reinforcement Learning in Games: History-Aware Training for Improved Stability

M Wright, Y Wang, and MP Wellman Proceedings of the 20th ACM Conference on Economics and Computation, pages 617-636, June 2019. Abstract Deep reinforcement learning (RL) is a powerful method for generating policies in complex environments,…
Mason Wright
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Mason Wright defends thesis

Congratulations to Mason Wright, on a successful thesis defense. And a special thanks to Mason's thesis committee members: Grant Schoenebeck Demos Teneketzis Jenna Wiens
Mason Wright

Bounding regret in simulated games

S Jecmen, E Brinkman, and A Sinha 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. ICML-18 Workshop on Exploration in RL, July 2018. Abstract We present a bandit-style problem arising from a specific problem in agent-based…
Mason Wright

A Cloaking Mechanism to Mitigate Market Manipulation

X Wang, Y Vorobeychik, and MP Wellman 27th International Joint Conference on Artificial Intelligence, pages 541–547, July 2018. Abstract We propose a cloaking mechanism to deter spoofing, a form of manipulation in financial markets. The…