5 papers
Learning to Recommend in Unknown Games
Arwa Alanqary, Zakaria Baba, Manxi Wu +1
We study preference learning through recommendations in multi-agent game settings, where a moderator repeatedly interacts with agents whose utility functions are unknown. In each r…
Game-to-Real Gap: Quantifying the Effect of Model Misspecification in Network Games
Bryce L. Ferguson, Chinmay Maheshwari, Manxi Wu +1
Game-theoretic models and solution concepts provide rigorous tools for predicting collective behavior in multi-agent systems. In practice, however, different agents may rely on dif…
Average Unfairness in Routing Games
Pan-Yang Su, Arwa Alanqary, Bryce L. Ferguson +3
We propose average unfairness as a new measure of fairness in routing games, defined as the ratio between the average latency and the minimum latency experienced by users. This mea…
Convergence of Decentralized Actor-Critic Algorithm in General-sum Markov Games
Chinmay Maheshwari, Manxi Wu, Shankar Sastry
Markov games provide a powerful framework for modeling strategic multi-agent interactions in dynamic environments. Traditionally, convergence properties of decentralized learning a…
Adaptive Incentive Design with Learning Agents
Chinmay Maheshwari, Kshitij Kulkarni, Manxi Wu +1
We propose an adaptive incentive mechanism that learns the optimal incentives in environments where players continuously update their strategies. Our mechanism updates incentives b…