Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Nakhleh, Khaled"'
Simulation-Based Optimistic Policy Iteration For Multi-Agent MDPs with Kullback-Leibler Control Cost
This paper proposes an agent-based optimistic policy iteration (OPI) scheme for learning stationary optimal stochastic policies in multi-agent Markov Decision Processes (MDPs), in which agents incur a Kullback-Leibler (KL) divergence cost for their c
Externí odkaz:
http://arxiv.org/abs/2410.15156
This paper introduces a new theoretical framework for optimizing second-order behaviors of wireless networks. Unlike existing techniques for network utility maximization, which only consider first-order statistics, this framework models every random
Externí odkaz:
http://arxiv.org/abs/2407.15983
Autor:
Nakhleh, Khaled, Raza, Minahil, Tang, Mack, Andrews, Matthew, Boney, Rinu, Hadzic, Ilija, Lee, Jeongran, Mohajeri, Atefeh, Palyutina, Karina
We study the training performance of ROS local planners based on Reinforcement Learning (RL), and the trajectories they produce on real-world robots. We show that recent enhancements to the Soft Actor Critic (SAC) algorithm such as RAD and DrQ achiev
Externí odkaz:
http://arxiv.org/abs/2303.11801
Autor:
Nakhleh, Khaled, Hou, I-Hong
We consider the problem of learning the optimal threshold policy for control problems. Threshold policies make control decisions by evaluating whether an element of the system state exceeds a certain threshold, whose value is determined by other elem
Externí odkaz:
http://arxiv.org/abs/2209.08646
This paper introduces a new theoretical framework for optimizing second-order behaviors of wireless networks. Unlike existing techniques for network utility maximization, which only considers first-order statistics, this framework models every random
Externí odkaz:
http://arxiv.org/abs/2201.06486
Whittle index policy is a powerful tool to obtain asymptotically optimal solutions for the notoriously intractable problem of restless bandits. However, finding the Whittle indices remains a difficult problem for many practical restless bandits with
Externí odkaz:
http://arxiv.org/abs/2110.02128