275 citations · 344 across the 8 of their papers we have counts for
3 papers · 1 filter
Learning Optimal Resource Allocations in Wireless Systems
Mark Eisen, Clark Zhang, Luiz F. O. Chamon +2
This paper considers the design of optimal resource allocation policies in wireless communication systems which are generically modeled as a functional optimization problem with st…
Learning Implicit Sampling Distributions for Motion Planning
Clark Zhang, Jinwook Huh, Daniel D. Lee
Sampling-based motion planners have experienced much success due to their ability to efficiently and evenly explore the state space. However, for many tasks, it may be more efficie…
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…