153 citations · 816 across the 54 of their papers we have counts for
5 papers · 2 filters
Finding Friend and Foe in Multi-Agent Games
Jack Serrino, Max Kleiman-Weiner, David C. Parkes +1
Recent breakthroughs in AI for multi-agent games like Go, Poker, and Dota, have seen great strides in recent years. Yet none of these games address the real-life challenge of coope…
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation
Zhe Feng, David C. Parkes, Haifeng Xu
Motivated by economic applications such as recommender systems, we study the behavior of stochastic bandits algorithms under \emph{strategic behavior} conducted by rational actors,…
Learning Representations by Humans, for Humans
Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji +2
When machine predictors can achieve higher performance than the human decision-makers they support, improving the performance of human decision-makers is often conflated with impro…
Weighted Tensor Completion for Time-Series Causal Inference
Debmalya Mandal, David Parkes
Marginal Structural Models (MSM) are the most popular models for causal inference from time-series observational data. However, they have two main drawbacks: (a) they do not captur…
Learning to Collaborate in Markov Decision Processes
Goran Radanovic, Rati Devidze, David C. Parkes +1
We consider a two-agent MDP framework where agents repeatedly solve a task in a collaborative setting. We study the problem of designing a learning algorithm for the first agent (A…