@@ -24,7 +24,7 @@ It can be used for many learning task where a two-dimensional grid could be the
Flatland delivers a python implementation which can be easily extended. And it provides different baselines for different environments.
Each environment enables an interesting task to solve. For example, the mutli-agent navigation task for railway train dispatching is a very exciting topic.
It can be easily extended or adapted to airplane landing problem. This can be the basic implementation for many other transportation planning task.
It can be easily extended or adapted to the airplane landing problem. This can be the basic implementation for many other transportation planning task.
The railway environment has a very restricted transition behaviour. Trains can normally not run backwards and the have to follow rails.
The can only switch cells along rails or the pass a switch in right direction. Thus the navigation behaviour of a train is very restricted.
The planning problem where many agents share same infrastructure becomes mostly to an ordering problem.
