3 papers
cs.MA2025
Policy Optimization in Multi-Agent Settings under Partially Observable Environments
Ainur Zhaikhan, Malek Khammassi, Ali H. Sayed
This work leverages adaptive social learning to estimate partially observable global states in multi-agent reinforcement learning (MARL) problems. Unlike existing methods, the prop…
cs.NI2025
Energy-as-a-Service for RF-Powered IoE Networks: A Percolation Theory Approach
Hao Lin, Ainur Zhaikhan, Mustafa A. Kishk +2
Due to the involved massive number of devices, radio frequency (RF) energy harvesting is indispensable to realize the foreseen Internet-of-Everything (IoE) within 6G networks. Anal…
cs.LG2024
Multi-agent Off-policy Actor-Critic Reinforcement Learning for Partially Observable Environments
Ainur Zhaikhan, Ali H. Sayed
This study proposes the use of a social learning method to estimate a global state within a multi-agent off-policy actor-critic algorithm for reinforcement learning (RL) operating…