@@ -24,7 +24,7 @@ The **tmc.py** file defines a **class TransitionMatrixCalculator** that calcula
### 2. markovDecison.py
The **markovDecison.py** file contains a **class MarkovDecisionProcess** that defines the Value Iteration algorithms for the different strategies. The **solve** function is used to calculate the optimal policy by the Value Iteration algorithm. This is achieved by using the 3 functions **_compute_vi_safe**,*_compute_vi_normal**,**_compute_vi_risky** which make it possible to calculate the Value Iteration for each of the dice and choose the minimum of all the values. Then, the **markovDecision** function using the **solve** function displays the optimal strategy (the dice to be played according to a layout) and the theoretical cost of each square according to a cyclic or acyclic game.
The **markovDecison.py** file contains a **class MarkovDecisionProcess** that defines the Value Iteration algorithms for the different strategies. The **solve** function is used to calculate the optimal policy by the Value Iteration algorithm. This is achieved by using the 3 functions **_compute_vi_safe**,**_compute_vi_normal**,**_compute_vi_risky** which make it possible to calculate the Value Iteration for each of the dice and choose the minimum of all the values. Then, the **markovDecision** function using the **solve** function displays the optimal strategy (the dice to be played according to a layout) and the theoretical cost of each square according to a cyclic or acyclic game.
