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 |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
13 |
14 |
15 |
| P(sense door | location) |
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 |
| P(sense light | location) |
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 |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
13 |
14 |
15 |
| P(new location | old location = 0, action = move right) |
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 |
|
