4 papers
Facilitating Sim-to-real by Intrinsic Stochasticity of Real-Time Simulation in Reinforcement Learning for Robot Manipulation
Ram Dershan, Amir M. Soufi Enayati, Zengjie Zhang +2
Simulation is essential to reinforcement learning (RL) before implementation in the real world, especially for safety-critical applications like robot manipulation. Conventionally,…
Robust distributed linear programming
Dean Richert, Jorge Cortes
This paper presents a robust, distributed algorithm to solve general linear programs. The algorithm design builds on the characterization of the solutions of the linear program as…
Distributed bargaining in dyadic-exchange networks
Dean Richert, Jorge Cortes
This paper considers dyadic-exchange networks in which individual agents autonomously form coalitions of size two and agree on how to split a transferable utility. Valid results fo…
Distributed linear programming with event-triggered communication
Dean Richert, Jorge Cortes
We consider a network of agents whose objective is for the aggregate of their states to converge to a solution of a linear program in standard form. Each agent has limited informat…