In recent years, Deep Reinforcement Learning (DRL) algorithms have achieved state-of-the-
art performance in many challenging strategy games. Because these games have …

This paper addresses the load restoration problem after power outage events. Our primary
proposed methodology is using multi-agent deep reinforcement learning to optimize the …

There are relatively few conventions followed in reinforcement learning (RL) environments
to structure the action spaces. As a consequence the application of RL algorithms to tasks …

This paper addresses the load restoration problem after a power outage event. Our primary
proposed methodology uses a multi-agent reinforcement learning method to make the …

Behavior cloning (BC) techniques that combine self-play capabilities with imitation learning
from experts to refine self-play models have shown performance improvement in robotics …

Real-time Strategy (RTS) games provide a challenging environment for AI research, due to
their large state and action spaces, hidden information, and real-time gameplay. The RTS …

Real-time Strategy (RTS) games provide a challenging environment for AI research, due to
their large state and action spaces, hidden information, and real-time gameplay. Star-Craft II …