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We now add an additional degree of non-determinism and allow transitions that can be taken independent of the input-ε-transitions.
Here whenever the automaton is in state 1 it may make a transition to state 3 without consuming any input. Similarly, if it is in state 0 it may make such a transition to state 2. The advantage of such transitions is that they allow one to build NFAs in pieces, with each piece handling some portion of the language, and then splice the pieces together to form an automaton handling the entire language. To accommodate these transitions we need to modify the type of the transition relation to allow edges labeled ε.
In general non-determinism, by introducing a degree of parallelism, may increase the accepting power of a model of computation. But if we subject NFAs to the same sort of analysis
phases of operational reaserch
a) Let n be the pumping lemma constant. Then if L is regular, PL implies that s can be decomposed into xyz, |y| > 0, |xy| ≤n, such that xy i z is in L for all i ≥0. Since the le
The initial ID of the automaton given in Figure 3, running on input ‘aabbba' is (A, aabbba) The ID after the ?rst three transitions of the computation is (F, bba) The p
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
The Universality Problem is the dual of the emptiness problem: is L(A) = Σ∗? It can be solved by minor variations of any one of the algorithms for Emptiness or (with a little le
Computation of a DFA or NFA without ε-transitions An ID (q 1 ,w 1 ) computes (qn,wn) in A = (Q,Σ, T, q 0 , F) (in zero or more steps) if there is a sequence of IDs (q 1
These assumptions hold for addition, for instance. Every instance of addition has a unique solution. Each instance is a pair of numbers and the possible solutions include any third
unification algorithm
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