Question 1. (2 pts.) Match each AI problem description to the class of technique best suited to
the problem by entering the letter corresponding to the best technique into the blank. You will
not use a technique more than once. You do not need to solve the problems.
(i.) A robot must navigate a collapsed mine looking
for survivors. If it falls down a shaft it will be
destroyed. Air breezes are detectable next to most
shafts, but breezes aren’t always detected even
when they are present. The rough terrain means that
the robot’s movements are unreliable.
(ii.) The traffic on I-85 is unobservable from my
office, but I would like to infer the probability of a
traffic jam by observing the amount of honking
horns. Of course, people honk their horns for lots of
reasons. You also know that traffic is influenced by
rain, sporting events, and time of day. You also
know that once the traffic is jammed it tends to stay
jammed, and if there is no traffic jam it can
suddenly become jammed.
(iii.) Infer the probability that a patient has colon
cancer without running expensive tests. You are
able to make direct observations of symptoms:
diarrhea, fatigue, and weight loss. The probability of
this cancer is affected by the city you live in, your
diet, and genetic factors.
(iv.) Suppose you need to assemble a piece of Ikea
furniture but lost the instructions. Find a sequence
of operations that transform the pile of parts into
fully assembled furniture. Assume the problem is
fully observable and that each operation cannot fail.
(v). Classifying rodents found on campus by
species. There are 3 types of rodents (rat, shrew, or,
mouse) that can be identified by inspecting size,
color, tail length, whisker length, and size of front
teeth. You must consider that any of these attributes
can take on a range of values (e.g., a baby rat could
be the size of a full-grown mouse).
(vi). An agent that can play tic-tac-toe against a
6-year old child. The child can be assumed to play
completely randomly, meaning it has equal
chance of marking any open cell.
(c) Markov decision process
(d) Partially-observable MDP
(e) Dynamic Bayesian network
(f) Bayesian inference
(g) Simulated annealing
Question 2. Suppose a person named Zeb who is a US citizen is playing a massive-multiplayer
fantasy role-playing game made by a US company. The game company has developed a new AI
system that uses a neural network trained on a massive amount of text from the internet to create
a dialogue system so that players can talk with virtual, AI-controlled players. Included in this
data is financial investing discussions from a social media platform called Reddit that allows
anyone to talk to anyone else about any topic. The dialogue system is still experimental and
players must agree to opt in. Zeb has been offered the terms of service and has opted in. Further,
Zeb talks to an AI-controlled character who recommends investing in a particular stock. Zeb
ends up losing a large amount of money. Who can Zeb hold liable?
2.a. (1 point) Give one entity (including the possibility of the AI system itself) that might be held
liable in the US legal system. Provide a justification.
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