CSC242: Introduction to Artificial Intelligence
Homework 1: AIMA Chapter 1
1. Describe in one sentence each the following approaches to creating artificial (computational) intelligences:
(a) Acting humanly
Solution: Focus on developing systems that can participate in activities (e.g.,
conversation) indistinguishably from humans, regardless of how such behavior
is implemented internally.
(b) Thinking humanly
Solution: Develop intelligent systems by modeling how the human mind works,
insofar as we understand this through psychological and neurological experiments.
(c) Thinking rationally
Solution: Use logical reasoning to compute “correct” conclusions (something
humans do at least some of the time when behaving intelligently).
(d) Acting rationally
Solution: Develop systems that act rationally, in the sense of making appropriate choices (maximizing expected outcome) even when these cannot (always)
be inferred deductively.
Note that these are not mutually exclusive!
2. What makes the Turing Test a good test of intelligence? In what ways is it lacking?
Solution: Pro: The TT requires language, knowledge, reasoning, learning, and so
on, which are abilities that we associate with intelligence (intelligent behavior). The
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TT places no constraints on the subjects of conversation, allowing the examiner to
probe any aspect of human existence.
Con: Original version (arguably) ignored perception and physical world. There is
debate about whether being able to “fool” someone is sufficient as a test of intelligence. Duplicating human behavior may not necessarily be the way to go (classic
example of this is pursing flight by copying birds vs. achieving powered flight using
the aerodynamics of airfoils as in airplanes).
3. True or false: Cognitive Science combines computer models from AI with experimental
techniques from Psychology, Neuroscience, and Linguistics to develop testable theories
of the human mind.
Solution: True
4. Describe the two main obstacles of the logical approach to AI. Are these obstacles only
for logic?
Solution: It is hard to put informal knowledge in formal (i.e., logical) terms. It
is hard to do inference in practice (in fact, impossible in Gödel’s sense, even in
principle). Since computer programs are formal languages, these are problems for
any computational model of intelligence.
5. Briefly distinguish rational action from logical inference. Is perfect rationality feasible?
Solution: An agent can’t always decide what to do by reasoning purely logically
(deductively). That is, what to do is not always a deductive consequence of the
agents’ beliefs. Nonetheless, the agent still has to choose what to do in order to
achieve the best outcome. Perfect rationality is mathematically well-defined, but
(a) it may not match human intuitions about intelligent behavior, and (b) it is
computationally intractable anyway. We’ll see all these concepts in more detail later
in the course.
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