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Depending upon the nature of the problem, the solution strategy has to be decided or modified. For example, a b Elementary Algorithmics While proving a theorem, if an unrequired lemma is proved, we may ignore it. The only loss is the loss of efforts in proving the lemma. Such a problem is called ignorable-step problem.
Suppose we are interested Mcs 031 solving 8-puzzle problem of reaching from some initial state say 2 8 7 1 3 5 6 4 to some final state say 1 2 3 8 4 7 6 5 by sliding, any one of the digits from a cell adjacent to the blank cell, to the blank cell.
Then a wrong step cannot be ignored but has to be recovered. By recoverable, we mean that we are allowed to move back to the earlier state from which we came to the current state, if current state seems to be less desirable than the earlier state.
The 8puzzle problem has recoverable steps, or, we may say the problem is a recoverable problem c However if, we are playing chess, then a wrong step may not be even recoverable.
Such a problem is called an irrecoverable step problem. Depending on the nature of the problem as ignorable-step, recoverable-step or irrecoverable-step problem, we have to choose our tools, techniques and strategies for solving the problem. For example, for ignorable-step problems, simple control structures for sequencing and iteration may be sufficient.
However, if the problem additionally has recoverablestep possibilities then facilities like back-tracking, as are available in the programming language PROLOG, may have to be used. Further, if the problem additionally has irrecoverable-step possibilities then planning tools should be available in the computer system, so that entire sequence of steps may be analyzed in advance to find out where the sequence may lead to, before the first step is actually taken.
There are many other characteristics of a problem viz. Most of the computer systems used for educational purposes are PCs based on VonNeumann architecture. Algorithms, that are designed to be executed on such machines are called sequential algorithms. However, we restrict ourselves to sequential algorithms only.
We have to determine in advance what approximation is acceptable, e. Also, there are problems, for which finding the exact solutions may be possible, but the cost or complexity, to be defined later may be too much.
In the case of such problems, unless it is absolutely essential, it is better to use an alternative algorithm which gives reasonably approximate solution, which otherwise may not be exact. For example, consider the Travelling Salesperson Problem: A salesperson has a list of, say n cities, each of which he must visit exactly once.
There are direct roads between each pair of the given cities. Find the shortest possible route that takes the salesperson on the round trip starting and finishing in any one of the n cities and visiting other cities exactly once.
In order to find the shortest paths, one should find the cost of covering each of the n! Even for a problem of visiting 10 cities, n! In a country like India, a travelling salesperson may be expected to visit even more than 10 cities. To find out exact solution in such cases, though possible, is very time consuming.
In such case, a reasonably good approximate solution may be more desirable. In a later paradigm of problem-solving viz. For each problem domain, a particular set of techniques have been found more useful, though other techniques also may be gainfully employed.
A major part of the material of the course, deals with the study of various techniques and their suitability for various types of problem domains. Such a study can be a useful guide for solving new problems or new problems types.Hire Jumping Castles in durban, Party planning, hire rides for kids in durban, Kiddies parties, Party services, Hire Costumes, Catering services, Durban Hire.
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