(When) Are Contrastive Explanations of Reinforcement Learning Helpful?

no code implementations • 14 Nov 2022 • Sanjana Narayanan, Isaac Lage, Finale Doshi-Velez

We find that complete explanations are generally more effective when they are the same size or smaller than a contrastive explanation of the same policy, and no worse when they are larger.

reinforcement-learning Reinforcement Learning (RL)

On Learning Prediction-Focused Mixtures

no code implementations • 25 Oct 2021 • Abhishek Sharma, Catherine Zeng, Sanjana Narayanan, Sonali Parbhoo, Finale Doshi-Velez

Probabilistic models help us encode latent structures that both model the data and are ideally also useful for specific downstream tasks.

Time Series Time Series Analysis