Let us examine the rationality of various vacuum-cleaner agent functions.

a. Show that the simple vacuum-cleaner agent function described in Figure 2.3 is indeed rational under the assumptions listed on page 38.

b. Describe a rational agent function for the case in which each movement costs one point. Does the corresponding agent program require internal state?

c. Discuss possible agent designs for the cases in which clean squares can become dirty and the geography of the environment is unknown. Does it make sense for the agent to learn from its experience in these cases? If so, what should it learn? If not, why not?

Figure 2.3

Transcribed Image Text:

Percept sequence Action [A, Clean] [A, Dirty] [B, Clean] [B, Dirty] [A, Clean], [A, Clean] [A, Clean], [A, Dirty] Right Suck Left Suck Right Suck [A, Clean]. [A, Clean], [A, Clean] [A, Clean], [A, Clean], [A, Dirty] Right Suck