I want to make this a little bit more beautiful. I will introduce a variable called “world,” and for each of the 5 grid cells, world specifies the color of the cell– green, red, red, green, green. Further, I define the measurement Z to be red. Can you define a function, called “sense,” which is the measurement update, which takes as input the initial distribution p and the measurement Z and all the other global variables and outputs a normalized distribution called “Q” in which Q reflects the non-normalized product of our input probability, which will be 0.2 and so on, and the corresponding pHit or pMiss in accordance to whether these colors over here agree or disagree? When I call sense(p, Z), I expect to get the vector as output as before, but now in the form of a function. The reason I’d like to have a function here is because later on as we build our localizer we will apply this to every single measurement over and over again. This function should really respond to any arbitrary p and arbitrary Z, either red or green, and give me the non-normalized Q, which gives me the vector 0.04 or 0.12 and so on and so on.