1 citations · 1 across the 4 of their papers we have counts for
4 papers
Fixing Incomplete Value Function Decomposition for Multi-Agent Reinforcement Learning
Andrea Baisero, Rupali Bhati, Shuo Liu +2
Value function decomposition methods for cooperative multi-agent reinforcement learning compose joint values from individual per-agent utilities, and train them using a joint objec…
Curriculum Learning for Cooperation in Multi-Agent Reinforcement Learning
Rupali Bhati, Sai Krishna Gottipati, Clodéric Mars +1
While there has been significant progress in curriculum learning and continuous learning for training agents to generalize across a wide variety of environments in the context of s…
Interpret Your Care: Predicting the Evolution of Symptoms for Cancer Patients
Rupali Bhati, Jennifer Jones, Audrey Durand
Cancer treatment is an arduous process for patients and causes many side-effects during and post-treatment. The treatment can affect almost all body systems and result in pain, fat…
ACReL: Adversarial Conditional value-at-risk Reinforcement Learning
M. Godbout, M. Heuillet, S. Chandra +2
In the classical Reinforcement Learning (RL) setting, one aims to find a policy that maximizes its expected return. This objective may be inappropriate in safety-critical domains s…