The past decade has witnessed a significant growth of electric vehicles (EVs) deployment in public and private transportation sectors. Dynamic electric vehicle routing aims to plan the routes of EVs to serve dynamically generated customers’ requests while ensuring the battery level by visiting the r...

Deep reinforcement learning methods have shown great performance on many challenging cooperative multi-agent tasks. Two main promising research directions are multi-agent value function decomposition and multi-agent policy gradients. In this paper, we propose a new decomposed multi-agent soft actor-...

Reinforcement learning in multi-agent scenarios is important for real-world applications but presents challenges beyond those seen in single-agent settings. We present an actor-critic algorithm that trains decentralized policies in multi-agent settings, using centrally computed critics that share an...

Active distribution network is encountering serious voltage violations associated with the proliferation of distributed photovoltaic. Cutting-edge research has confirmed that voltage regulation techniques based on deep reinforcement learning manifest superior performance in addressing this issue. Ho...