Floyd-Warshall Reinforcement Learning: Learning from Past Experiences to Reach New Goals

Understand

Consider mutli-goal tasks that involve static environments and dynamic goals.

• Examples of such tasks, such as goal-directed navigation and pick-and-place in robotics, abound.
• Two types of Reinforcement Learning (RL) algorithms are used for such tasks: model-free or model-based.
• Each of these approaches has limitations.