Kamil Ciosek

Multi-task Batch Reinforcement Learning with Metric Learning

2019 · arXiv (Cornell University)

We tackle the Multi-task Batch Reinforcement Learning problem. Given multiple datasets collected from different tasks, we train a multi-task policy to perform well in unseen tasks sampled from the same distribution. The task identities of …

Regularized Policies are Reward Robust

2021 · arXiv (Cornell University)

Entropic regularization of policies in Reinforcement Learning (RL) is a commonly used heuristic to ensure that the learned policy explores the state-space sufficiently before overfitting to a local optimal policy. The primary motivation for using …

Automatic Music Playlist Generation via Simulation-based Reinforcement Learning

2023

Personalization of playlists is a common feature in music streaming services, but conventional techniques, such as collaborative filtering, rely on explicit assumptions regarding content quality to learn how to make recommendations. Such assumptions often result …