How to implement pathfinding and congestion detection with neural network?
<p><a href="https://i.stack.imgur.com/LNvDq.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/LNvDq.png" alt="Conveyor layout. A and B entry points and C and D exit points. There is a crossroad at position X"></a></p>

<p>This is a conveyor system. Boxes enter the system at A and move towards C where they exit the system. The same goes for B->D.</p>

<p>Boxes on path A->C have higher priority than boxes B->D. Boxes can stop and wait in each square. If there is a box on A2 and also on B2, the one from A2 should go through X first.</p>

<p>If there are boxes on C2, C1, A2 and B2 then the box from B2 should go through X and box on A2 shuold wait, until C1 is empty. Otherwise it would block the path B->D.</p>

<p><strong>How can I solve this problem with neural networks?</strong>
So for every turn I would like to input the current state of each block and as a result I would like to get from where to where the next box should move.</p>

<p>For example:
System state: <em>BOX present at A1</em>
Result: <em>A1, A2</em></p>

<p>I don't know if neural networks are a good tool for this problem, but I am just curious. 
Thanks for input :)</p>