## Investigating Practical Ordering of Grids

In Reinforcement Learning there is an environment known as Gridworld. In this environment you have a grid and there is an agent that learns how to find the shortest path from one cell to another. The theme of reinforcement learning is that you do not want to hard-code the rules, but you want the agent to explore until it can find a set of moves that are optimal for the problem at hand. Usually you can alter the grids to make the tasks tough–set ‘traps’, add obstacles, etc. We are considering grids with obstacles, and an interesting question that came up is the following,

Given two grids of size , say which have respectively obstacles where , what are reasonable ways to put an order on the ‘complexity’ of the grids?

In other words, we want to be able to say that, for instance, in the agent will find the optimal path more easily than in given any two grids .…