Ridesharing has been emerging as a new type of mobility. However, the early promises of
ridesharing for alleviating congestion in cities may be undermined by a number of …

Multi-agent Reinforcement Learning (RL) is frequently used in large-scale autonomous
systems to learn the behaviours that best suit the system's operating environment. Learning …

Reinforcement learning (RL) is increasingly used to achieve adaptive behaviours in Internet
of Things systems relying on large amounts of sensor data. To address the need for self …

Recent research has shown the potential of using available mobile fog devices (such as
smartphones, drones, domestic and industrial robots) as relays to minimize communication …

With increasing applications of reinforcement learning in real life problems, it is becoming
essential that agents are able to update their knowledge continually. Lifelong learning …

The development of more sophisticated autonomous course-determination mechanisms for
Autonomous Mobility-on-Demand systems is an active area of research and development. In …