For our week 2 progress, our group decided to learn about algorithms that would be suitable for our congklak final project. Currently, we are debating on using 2 different algorithms. Random forest and Partially Observable Markov Decision Process.

Random Forest Algorithms
Random forest or Random Decision Forest is a method that operates by constructing multiple Decision Trees during 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 which 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.