Write the conditional probability tables for the sensing model. Also provide the state probability distribution according to the dynamics model, given that the previous state was position 0 and the previous action was to move right.
• The dynamics model is given by the following table. Notice that since "sense door" and "sense light" are Boolean variables with 2-element domains, the identities P(¬sense door | location) = 1 - P(sense door | location) and P(¬sense light | location) = 1 - P(sense light | location) are implied. Hence, we save half of the work by omitting the negation probabilites.  location P(sense door | location) P(sense light | location) 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 0.1 0.1 0.8 0.1 0.8 0.1 0.1 0.8 0.1 0.1 0.1 0.8 0.1 0.1 0.1 0.1 0.1 0.05 0.05 0.05 0.1 0.2 0.4 0.6 0.8 0.95 0.99 0.95 0.8 0.6 0.4 0.2

• The following table describes the requested portion of the dynamics model. The complete dynamics model follows a similar pattern, but would require 2*16*16 = 512 table entries, one for each ordered triple (new location, old location, action).  new location P(new location | old location = 0, action = move right) 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 0.1 0.8 0.074 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002