3 papers
cs.NE2026
Deep Neural Network-guided PSO for Tracking a Global Optimal Position in Complex Dynamic Environment
Stephen Raharja, Toshiharu Sugawara
We propose novel particle swarm optimization (PSO) variants incorporated with deep neural networks (DNNs) for particles to pursue globally optimal positions in dynamic environments…
cs.AI2025
Robust and Efficient Communication in Multi-Agent Reinforcement Learning
Zejiao Liu, Yi Li, Jiali Wang +6
Multi-agent reinforcement learning (MARL) has made significant strides in enabling coordinated behaviors among autonomous agents. However, most existing approaches assume that comm…
cs.MA2024
Reducing Redundant Computation in Multi-Agent Coordination through Locally Centralized Execution
Yidong Bai, Toshiharu Sugawara
In multi-agent reinforcement learning, decentralized execution is a common approach, yet it suffers from the redundant computation problem. This occurs when multiple agents redunda…