6 papers · 1 filter
Counterfactual Shapley Credit Assignment
Mingxuan Li, Kai-Zhan Lee, Elias Bareinboim
The Credit Assignment Problem (CAP) is fundamental to developing efficient and explainable Reinforcement Learning (RL) agents. Existing frameworks, whether relying on temporal cont…
Scalable Causal Imitation Learning
Eylam Tagor, Mingxuan Li, Elias Bareinboim
Imitation learning enables learning a policy in an unknown environment with a latent reward signal using expert demonstrations, but it struggles when the imitator's and expert's ob…
Confounding Robust Continuous Control via Automatic Reward Shaping
Mateo Juliani, Mingxuan Li, Elias Bareinboim
Reward shaping has been applied widely to accelerate Reinforcement Learning (RL) agents' training. However, a principled way of designing effective reward shaping functions, especi…
Causal Flow Q-Learning for Robust Offline Reinforcement Learning
Mingxuan Li, Junzhe Zhang, Elias Bareinboim
Expressive policies based on flow-matching have been successfully applied in reinforcement learning (RL) more recently due to their ability to model complex action distributions fr…
Causally Aligned Curriculum Learning
Mingxuan Li, Junzhe Zhang, Elias Bareinboim
A pervasive challenge in Reinforcement Learning (RL) is the "curse of dimensionality" which is the exponential growth in the state-action space when optimizing a high-dimensional t…
Measuring Fairness in Financial Transaction Machine Learning Models
Deniz Sezin Ayvaz, Lorenzo Belenguer, Hankun He +12
Mastercard, a global leader in financial services, develops and deploys machine learning models aimed at optimizing card usage and preventing attrition through advanced predictive…