The tree observations is build by exploiting the graph structure of the railway network. The observation is generated by spanning a **4 branched tree** from the current position of the agent. Each branch follows the allowed transitions (backward branch only allowed at dead-ends) untill a cell with multiple allowed transitions is reached. Here the information gathered along the branch is stored as a node in the tree.
The tree observations is build by exploiting the graph structure of the railway network. The observation is generated by spanning a **4 branched tree** from the current position of the agent. Each branch follows the allowed transitions (backward branch only allowed at dead-ends) untill a cell with multiple allowed transitions is reached. Here the information gathered along the branch is stored as a node in the tree.
Figure bellow illustrates how such a tree observation is build:
Figure bellow illustrates how such a tree observation is build:
1. From Agent location probe all 4 directions (``L:Blue``, ``F:Green``,``R:Purple``,``B:Red``) starting with left and start branches when transition is allowed.
1. From Agent location probe all 4 directions (``L:Blue``, ``F:Green``,``R:Purple``,``B:Red``) starting with left and start branches when transition is allowed.
1. For each branch walk along the allowed transition till you reach a dead-end, switch or the target destination.
1. For each branch walk along the allowed transition till you reach a dead-end, switch or the target destination.
2. Create a node an fill in node information as stated below.
2. Create a node an fill in node information as stated below.
