4 citations · 4 across the 2 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2019
Sufficiently Accurate Model Learning
Clark Zhang, Arbaaz Khan, Santiago Paternain +1
Modeling how a robot interacts with the environment around it is an important prerequisite for designing control and planning algorithms. In fact, the performance of controllers an…
cs.LG2018
Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients
Arbaaz Khan, Clark Zhang, Daniel D. Lee +2
In this paper, we explore using deep reinforcement learning for problems with multiple agents. Most existing methods for deep multi-agent reinforcement learning consider only a sma…