4 papers
Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning
Zhiyao Zhang, Myeung Suk Oh, FNU Hairi +3
Actor-critic methods for decentralized multi-agent reinforcement learning (MARL) facilitate collaborative optimal decision making without centralized coordination, thus enabling a…
Consensus-based Decentralized Multi-agent Reinforcement Learning for Random Access Network Optimization
Myeung Suk Oh, Zhiyao Zhang, FNU Hairi +2
With wireless devices increasingly forming a unified smart network for seamless, user-friendly operations, random access (RA) medium access control (MAC) design is considered a key…
Byzantine-Resilient Decentralized Multi-Armed Bandits
Jingxuan Zhu, Alec Koppel, Alvaro Velasquez +1
In decentralized cooperative multi-armed bandits (MAB), each agent observes a distinct stream of rewards, and seeks to exchange information with others to select a sequence of arms…
On the Hardness of Decentralized Multi-Agent Policy Evaluation under Byzantine Attacks
Hairi, Minghong Fang, Zifan Zhang +2
In this paper, we study a fully-decentralized multi-agent policy evaluation problem, which is an important sub-problem in cooperative multi-agent reinforcement learning, in the pre…