lab2 with crocprob vector and sparse TPtable

" What you should do is this:
1. Multiply your previous state estimation vector (which has the probability of croc being at each node at the previous time) by your transition matrix, getting a new state estimation vector assigning a probability of croc being at each node now.
2. For each node, multiply the entry in the new state estimation vector by the probability of obtaining the given observations if croc is at that node. (I.e. what you calculated above.) Your state estimation vector now no longer sums to 1.
>> * Normalize the transition probability table. 
Now you normalize the new state estimation vector so that it does sum to 1.
>> * Find the highest element in the transition probability table and return its row index.
OK - but using the new state estimation vector, not the transition probability table.
>> * Do action depending on the amount of steps between playerLoc and guessed location: walk/walk, walk/search or simply search.
Right, assuming you know the paths you need to take to get to where you are trying to get to. This requires implementing a path finding algorithm.
>> * repeat if croc not found.
Good"