INFORMED SEARCH
When more information than the initial state, the operators, and
the goal available, the size of the search space can usually be
constrained. When this is the case, the better the information available,
the more efficient the search process will be. Such methods are
known as informed search methods. They often depend on the use of
heuristic information.
Heuristic Information
Q. Describe briefly the following A.I. technique:
Heuristics (June 99, June 02, June 03) |
Ans. Heuristic is a rule of thumb or judgmental technique
that leads to a solution some of the time but provides no
guarantee of success. It may in fact end in failure. Heuristic
are usually acquired with much experience. For example, in
locating a fault in a TV set, an experienced technician will
not start by making numerous voltage checks when it is clear
that the sound is present but the picture is not, but instead
will immediately reason that the high voltage flyback transformer
or related component is the culprit. This type of reasoning
may not always be correct, but it frequently is, and then
leads to a quick solution.
Heuristics play an important role in search strategies because
of the exponential nature of most problems. They help to reduce
the number of alternatives from an exponential number to a
polynomial number and, thereby, obtain in a tolerable amount
of time. When exhaustive search is impractical, it is necessary
to compromise for a constrained search which eliminates many
paths but offers the promise of success some of the time.
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Informed Search methods
Q. Enumerate various informed search methods used in
AI. What do you understand by 'Heuristics'? What is the role
of 'Heuristics' in informed search? (Jan. 01, June 03) |
Ans. Various informed search methods used in AI are
listed below:
- Hill Climbing Methods
- Best-First Search
- Branch-and-Bound Search
- A* Search
Please refer to the previous question for more info.
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