We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
My research focus is on using continuous state partially observable Markov decision processes (POMDPs) to perform object manipulation tasks using a robotic arm. During object mani...
Decentralized planning in uncertain environments is a complex task generally dealt with by using a decision-theoretic approach, mainly through the framework of Decentralized Parti...
This paper considers a scenario in which a secondary user makes opportunistic use of a channel allocated to some primary network. The primary network operates in a time-slotted ma...
Anh Tuan Hoang, Ying-Chang Liang, David Tung Chong...