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 ...
The coexistence of two unlicensed links is considered, where one link interferes with the transmission of the other, over a timevarying, block-fading channel. In the absence of fa...
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...
This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
Bharaneedharan Rathnasabapathy, Piotr J. Gmytrasie...
Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...