1 citations · 1 across the 3 of their papers we have counts for
3 papers
Coagent Networks: Generalized and Scaled
James E. Kostas, Scott M. Jordan, Yash Chandak +5
Coagent networks for reinforcement learning (RL) [Thomas and Barto, 2011] provide a powerful and flexible framework for deriving principled learning rules for arbitrary stochastic…
Personalized Detection of Cognitive Biases in Actions of Users from Their Logs: Anchoring and Recency Biases
Atanu R Sinha, Navita Goyal, Sunny Dhamnani +4
Cognitive biases are mental shortcuts humans use in dealing with information and the environment, and which result in biased actions and behaviors (or, actions), unbeknownst to the…
Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning
Tong Mu, Georgios Theocharous, David Arbour +1
Online reinforcement learning (RL) algorithms are often difficult to deploy in complex human-facing applications as they may learn slowly and have poor early performance. To addres…