Safer model-based reinforcement learning for motion planning in autonomous inland shipping.

Currently, there is much research in the field of autonomous navigation. More recently, reinforcement learning (RL) is showing promising results in that field. A type of RL that shows great potential, called model-based RL has some considerable advantages over its model-free counterpart. Notably, it shows potential for safety improvement. Safety is one of the most important challenges that RL in autonomous navigation currently faces.

Keywords:ROBOTIC SYSTEM, MACHINE LEARNING

Disciplines:Adaptive agents and intelligent robotics, Machine learning and decision making, Artificial intelligence not elsewhere classified