12 citations · 67 across the 68 of their papers we have counts for
3 papers · 2 filters
Prediction and Control in Continual Reinforcement Learning
Nishanth Anand, Doina Precup
Temporal difference (TD) learning is often used to update the estimate of the value function which is used by RL agents to extract useful policies. In this paper, we focus on value…
DGFN: Double Generative Flow Networks
Elaine Lau, Nikhil Vemgal, Doina Precup +1
Deep learning is emerging as an effective tool in drug discovery, with potential applications in both predictive and generative models. Generative Flow Networks (GFlowNets/GFNs) ar…
Conditions on Preference Relations that Guarantee the Existence of Optimal Policies
Jonathan Colaço Carr, Prakash Panangaden, Doina Precup
Learning from Preferential Feedback (LfPF) plays an essential role in training Large Language Models, as well as certain types of interactive learning agents. However, a substantia…