For now, our members are still in the middle of deciding which algorithm that would be suitable for our Congklak final project. Right now, there are 2 choices of algorithms and we are still studying them, Random Forest and Partially Observable Markov Decision Process.

Random Forest Algorithm

Random Forest or Random Decision Forest is a method that operates by constructing multiple decision trees during the training phase. The decision of the majority of the trees is chosen by the Random Forest as the final decision.

Partially Observable Markov Decision Process

A POMDP is really just an MDP; we have a set of states, a set of actions, transitions and immediate rewards. The only difference is in whether or not we can observe the current state of the process. In a POMDP we add a set of observations to the model. So instead of directly observing the current state, the state gives us an observation that provides a hint about what state it is in. The observations can be probabilistic; so we need to also specify the observation model. This observation model simply tells us the probability of each observation for each state in the model.