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Nondeterministic Finite Automata. CS 130: Theory of Computation HMU textbook, Chapter 2 (Sec 2.3 & 2.5). NFAs: Nondeterministic Finite Automata. Same as a DFA, except:
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Nondeterministic Finite Automata CS 130: Theory of Computation HMU textbook, Chapter 2(Sec 2.3 & 2.5)
NFAs:Nondeterministic Finite Automata • Same as a DFA, except: • On input a, state q may have more than one transition out, implying the possibility of multiple choices when processing an input symbol • On input a, state q may have no transition out, implying the possibility of “being stuck” • A string w is acceptable as long as there exists an admissible state sequence for w
NFAs • A nondeterministic finite automaton M is a five-tuple M = (Q, , , q0, F), where: • Q is a finite set of states of M • is the finite input alphabet of M • : Q power set of Q, is the state transition function mapping a state-symbol pair to a subset of Q • q0 is the start state of M • F Q is the set of accepting states or final states of M
Example NFA • NFA that recognizes the language of strings that end in 01 0,1 Exercise:draw the complete transition table for this NFA 1 q2 0 q1 q0 note: (q0,0) = {q0,q1} (q1,0) = {}
^ definition for an NFA • ^: Q X * power set of Q • ^(q, ) = {q} • ^(q, w), w = xa(where x is a string and a is a symbol)is defined as follows: • Let ^(q, x) = {p1,p2,…pk} • Then, ^(q, w) = (pi, a)
Language recognized by an NFA • A string w is accepted by an NFA M if^(q0, w) F is non-empty • Note that ^(q0, w) represents a subset of states since the automaton is nondeterministic • Equivalent definition: there exists an admissible state sequence for w in M • The language L(M) recognized by an NFA is the set of strings accepted by M • L(M) ={ w | ^(q0, w) F is non-empty }
Converting NFAs to DFAs • Given a NFA, M = (Q, , , q0, F), build a DFA, M’ = (Q’, , ’, {q0}, F’) as follows. • Q’ contains all subsets S of states in Q. • The initial state of M’ is the set containing q0 • F’ is the set of all subsets of Q that contain at least one element in F (equivalently, the subset contains at least one final state)
Converting NFAs to DFAs • ’ is determined by putting together, for each state in the subset and each symbol, all states that may result from a transition:’(S, a) = (q, a)qS • May remove “unreachable” states in Q’
Example conversion • NFA • DFA 0,1 1 q2 0 q1 q0 1 0 1 0 {q0,q1} {q0,q2} {q0 } 0 1
NFA with -transitions • NFA that allows the transition of an empty string from a state • Jumping to a state is possible even without input • Revision on NFA definition simply allows the “symbol” for
NFA with -transitions • A nondeterministic finite automaton with -transitions (or -NFA) is a five-tupleM = (Q, , , q0, F), where: • Q is a finite set of states of M • is the finite input alphabet of M • : Q ( + ) power set of Q, is the state transition function mapping a state-symbol pair to a subset of Q • q0 is the start state of M • F Q is the set of accepting states or final states of M
Converting -NFAs to NFAs • Task: Given an-NFA M = (Q, , , q0, F), build aNFA M’ = (Q, , ’, q0, F’) • Need to eliminate -transitions • Need epsilon closure concept • Add transitions to enable transitions previously allowed by the -transitions • Note: the conversion process in the textbook instead builds a DFA from an -NFA • The conversion described in these slides is simpler
Epsilon closure • In an NFA M, let q Q • ECLOSE(q) represents all states r that can be reached from q using only -transitions • Recursive definition for ECLOSE • If (q, ) is empty, ECLOSE(q) = {q} • Else, Let (q, ) = {r1, r2,…, rn}.ECLOSE(q) = ECLOSE(ri) {q} • Note: check out constructive definition in the textbook
Additional transitions • Suppose ECLOSE(q) = {r1, r2,…, rn }. • For each transition from state ri tostate sj on (non-epsilon) symbol a,add a transition from qto sj on symbol a • That is,’(q, s) = (q, s) states resulting from the additional transitions • Initially set F’ = F.If (q, ) includes a state in F’, add q to F’
Equivalence of Finite Automata • Conversion processes betweenDFAs, NFAs, and -NFAs show that no additional expressive capacity (except convenience) is introduced by non-determinism or -transitions • All models represent regular languages • Note: possible exponential explosion of states when converting from NFA to DFA
Closure of Regular Languages under certain operations • Union L1 L2 • Complementation L1 • Intersection L1 L2 • Concatenation L1L2 • Goal: ensure a FA can be produced from the FAs of the “operand” languages
Finite Automata with Output • Moore Machines • Output symbol for each state encountered • Mealy Machines • Output symbol for each transition encountered • Exercise: formally define Moore and Mealy machines
Next: Regular Expressions • Defines languages in terms of symbols and operations • Example • (01)* +(10)* defines all even-length strings of alternating 0s and 1s • Regular expressions also model regular languages and we will demonstrate equivalence with finite automata