3 accepted papers
Multi-Agent Path Finding (MAPF) is an important issue in multi-agent cooperation. Many studies apply MultiAgent Reinforcement Learning (MARL) to solve MAPF in partially observable settings. The objective of cooperative MARL is to maximize the cumulative team reward. Nevertheless, in partially observ…
Trajectory prediction plays a crucial role in autonomous driving, but it is challenging due to the multi-modal nature of future trajectories. Behavior information is frequently employed to capture more diverse modalities of future trajectories. Traditional behavior information is typically hard-enco…
Anticipating the future behavior of pedestrians is a crucial part of deploying Automated Driving Systems (ADS) in urban traffic scenarios. Most recent works utilize a convolutional neural network (CNN) to extract visual information, which is then input to a recurrent neural network (RNN) along with…