Multi-Agent Reinforcement Learning for Connected and Automated Vehicles Control: Recent Advancements and Future Prospects
Connected and automated vehicles (CAVs) have emerged as a potential solution to the
future challenges of developing safe, efficient, and eco-friendly transportation systems …
future challenges of developing safe, efficient, and eco-friendly transportation systems …
When to switch: planning and learning for partially observable multi-agent pathfinding
Multi-agent pathfinding (MAPF) is a problem that involves finding a set of non-conflicting
paths for a set of agents confined to a graph. In this work, we study a MAPF setting, where …
paths for a set of agents confined to a graph. In this work, we study a MAPF setting, where …
Credit assignment in heterogeneous multi-agent reinforcement learning for fully cooperative tasks
Credit assignment poses a significant challenge in heterogeneous multi-agent
reinforcement learning (MARL) when tackling fully cooperative tasks. Existing MARL …
reinforcement learning (MARL) when tackling fully cooperative tasks. Existing MARL …
Graph Exploration for Effective Multiagent Q-Learning
A Zhaikhan, AH Sayed - IEEE Transactions on Neural …, 2024 - ieeexplore.ieee.org
This article proposes an exploration technique for multiagent reinforcement learning (MARL)
with graph-based communication among agents. We assume that the individual rewards …
with graph-based communication among agents. We assume that the individual rewards …