3 papers
cs.LG2025
Learning What to Do and What Not To Do: Offline Imitation from Expert and Undesirable Demonstrations
Huy Hoang, Tien Mai, Pradeep Varakantham +1
Offline imitation learning typically learns from expert and unlabeled demonstrations, yet often overlooks the valuable signal in explicitly undesirable behaviors. In this work, we…
cs.MA2022
Learning Individual Policies in Large Multi-agent Systems through Local Variance Minimization
Tanvi Verma, Pradeep Varakantham
In multi-agent systems with large number of agents, typically the contribution of each agent to the value of other agents is minimal (e.g., aggregation systems such as Uber, Delive…
cs.LG2018
Entropy based Independent Learning in Anonymous Multi-Agent Settings
Tanvi Verma, Pradeep Varakantham, Hoong Chuin Lau
Efficient sequential matching of supply and demand is a problem of interest in many online to offline services. For instance, Uber, Lyft, Grab for matching taxis to customers; Uber…