Robotics Reference
In-Depth Information
4. The machine must have or evolve concepts of partial success be-
cause on difficult problems decisive successes or failures come too
infrequently. The system should therefore be able to assess, for any
statement proved by the system, how near that statement is to (or
far from) a solution or proof.
5. The system must be able to create shortcuts. The learning of short-
cuts is complicated by the fact that the effect of a shortcut is not
usually good or bad in itself. Therefore, the mechanism within the
system that selects shortcuts should be able to identify interesting
or powerful shortcuts which might be useful to the system.
McCarthy illustrates the way the Advice Taker is supposed to act by
means of the following example. Assume that I am seated at my desk
at home and I wish to go to the airport. My car is parked at my home,
so to solve the problem I can walk to my car and drive it to the airport.
McCarthy's paper presents a formal statement of the premises used by
the Advice Taker as the basis for its solution to this problem and explains
the interpretation of each group of premises. Here I have paraphrased
his explanation for the sake of simplicity. The “program” presented by
McCarthy is written in the style of the programming language LISP, a
language conceived by McCarthy in 1956 during the Dartmouth work-
shop specifically for use in Artificial Intelligence work. 10
1. “ at(x,y) ” is a formal way of writing “x is at y”.
Under this heading we have the premises:
at(I, desk)
Meaning: I am at my desk.
at(desk,home)
Meaning: My desk is at my home.
at(car, home)
Meaning: My car is at my home.
at(home,county)
Meaning: My home is in a particular county.
10 LISP caters for computing with symbolic expressions (such as those in this example of the
Advice Taker) rather than with numbers, and it allows symbolic expressions and other information
to be represented in the computer's memory in the form of lists, hence the name “LISP” (for list
processing language).
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