57 citations · 62 across the 4 of their papers we have counts for
4 papers
Dissenting Explanations: Leveraging Disagreement to Reduce Model Overreliance
Omer Reingold, Judy Hanwen Shen, Aditi Talati
While explainability is a desirable characteristic of increasingly complex black-box models, modern explanation methods have been shown to be inconsistent and contradictory. The se…
PantheonRL: A MARL Library for Dynamic Training Interactions
Bidipta Sarkar, Aditi Talati, Andy Shih +1
We present PantheonRL, a multiagent reinforcement learning software package for dynamic training interactions such as round-robin, adaptive, and ad-hoc training. Our package is des…
APReL: A Library for Active Preference-based Reward Learning Algorithms
Erdem Bıyık, Aditi Talati, Dorsa Sadigh
Reward learning is a fundamental problem in human-robot interaction to have robots that operate in alignment with what their human user wants. Many preference-based learning algori…
When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans
Minae Kwon, Erdem Biyik, Aditi Talati +3
In order to collaborate safely and efficiently, robots need to anticipate how their human partners will behave. Some of today's robots model humans as if they were also robots, and…