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Computations are deliberate for processing information. Computability theory was discovered in the 1930s, and extended in the 1950s and 1960s. Its basic ideas have become part of the foundation that any computer scientist is expected to know. The study of computation intended for providing an insight into the characteristics of computations. Such an insight may be used for predicting the difficulty of desired computations, for selecting the approaches they should take, and for developing tools that facilitate their design. Study of computation also provides tools for identifying problems that can possibly be solved, as well as tools for designing such solutions that is the field of computer sciences deals with the development of methodologies for designing programs and with the development of computers for the implementation of programs.
The study of computability also develops precise and well-defined language for communicating perceptive thoughts about computations. It reveals that there are problems that cannot be solved. And of the problems that can be solved, there are some that require infeasible amount of resources (e.g., millions of years of computation time). These revelations might seem discouraging, but they have the benefit of warning against trying to solve such problems. The study of computation provides approaches for identifying such problems are also provided by the study of computation.
Computation should be studied through medium of programs because programs are descriptions of computations. The clear understanding of computation and programs requires clear discussion of the following concepts
• "Alphabets, Strings, and Representation • Formal languages and grammar• Programs• Problems• Reducibility among problems"
a finite automata accepting strings over {a,b} ending in abbbba
Our DFAs are required to have exactly one edge incident from each state for each input symbol so there is a unique next state for every current state and input symbol. Thus, the ne
It is not hard to see that ε-transitions do not add to the accepting power of the model. The underlying idea is that whenever an ID (q, σ v) directly computes another (p, v) via
A problem is said to be unsolvable if no algorithm can solve it. The problem is said to be undecidable if it is a decision problem and no algorithm can decide it. It should be note
The computation of an SL 2 automaton A = ( Σ, T) on a string w is the maximal sequence of IDs in which each sequential pair of IDs is related by |- A and which starts with the in
The objective of the remainder of this assignment is to get you thinking about the problem of recognizing strings given various restrictions to your model of computation. We will w
dfa for (00)*(11)*
design a tuning machine for penidrome
So we have that every language that can be constructed from SL languages using Boolean operations and concatenation (that is, every language in LTO) is recognizable but there are r
Another striking aspect of LTk transition graphs is that they are generally extremely ine?cient. All we really care about is whether a path through the graph leads to an accepting
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