Two-way finite automaton
In computer science, in particular in automata theory, a two-way finite automaton is a finite automaton that is allowed to re-read its input.
Two-way deterministic finite automaton
[edit]A two-way deterministic finite automaton (2DFA) is an abstract machine, a generalized version of the deterministic finite automaton (DFA) which can revisit characters already processed. As in a DFA, there are a finite number of states with transitions between them based on the current character, but each transition is also labelled with a value indicating whether the machine will move its position in the input to the left, right, or stay at the same position. Equivalently, 2DFAs can be seen as read-only Turing machines with no work tape, only a read-only input tape.
2DFAs were introduced in a seminal 1959 paper by Rabin and Scott,[1] who proved them to have equivalent power to one-way DFAs. That is, any formal language which can be recognized by a 2DFA can be recognized by a DFA which only examines and consumes each character in order. Since DFAs are obviously a special case of 2DFAs, this implies that both kinds of machines recognize precisely the class of regular languages. However, the equivalent DFA for a 2DFA may require exponentially many states, making 2DFAs a much more practical representation for algorithms for some common problems.
2DFAs are also equivalent to read-only Turing machines that use only a constant amount of space on their work tape, since any constant amount of information can be incorporated into the finite control state via a product construction (a state for each combination of work tape state and control state).
Formal description
[edit]Formally, a two-way deterministic finite automaton can be described by the following 8-tuple: where
- is the finite, non-empty set of states
- is the finite, non-empty set of input symbols
- is the left endmarker
- is the right endmarker
- is the start state
- is the end state
- is the reject state
In addition, the following two conditions must also be satisfied:
- For all
- for some
- for some
It says that there must be some transition possible when the pointer reaches either end of the input word.
- For all symbols [clarification needed]
It says that once the automaton reaches the accept or reject state, it stays in there forever and the pointer goes to the right most symbol and cycles there infinitely.[2]
Two-way nondeterministic finite automaton
[edit]A two-way nondeterministic finite automaton (2NFA) may have multiple transitions defined in the same configuration. Its transition function is
- .
Like a standard one-way NFA, a 2NFA accepts a string if at least one of the possible computations is accepting. Like the 2DFAs, the 2NFAs also accept only regular languages.
Two-way alternating finite automaton
[edit]A two-way alternating finite automaton (2AFA) is a two-way extension of an alternating finite automaton (AFA). Its state set is
- where .
States in and are called existential resp. universal. In an existential state a 2AFA nondeterministically chooses the next state like an NFA, and accepts if at least one of the resulting computations accepts. In a universal state 2AFA moves to all next states, and accepts if all the resulting computations accept.
State complexity tradeoffs
[edit]Two-way and one-way finite automata, deterministic and nondeterministic and alternating, accept the same class of regular languages. However, transforming an automaton of one type to an equivalent automaton of another type incurs a blow-up in the number of states. Christos Kapoutsis[3] determined that transforming an -state 2DFA to an equivalent DFA requires states in the worst case. If an -state 2DFA or a 2NFA is transformed to an NFA, the worst-case number of states required is . Ladner, Lipton and Stockmeyer.[4] proved that an -state 2AFA can be converted to a DFA with states. The 2AFA to NFA conversion requires states in the worst case, see Geffert and Okhotin.[5]
It is an open problem whether every 2NFA can be converted to a 2DFA with only a polynomial increase in the number of states. The problem was raised by Sakoda and Sipser,[6] who compared it to the P vs. NP problem in the computational complexity theory. Berman and Lingas[7] discovered a formal relation between this problem and the L vs. NL open problem, see Kapoutsis[8] for a precise relation.
Sweeping automata
[edit]Sweeping automata are 2DFAs of a special kind that process the input string by making alternating left-to-right and right-to-left sweeps, turning only at the endmarkers. Sipser[9] constructed a sequence of languages, each accepted by an n-state NFA, yet which is not accepted by any sweeping automata with fewer than states.
Two-way quantum finite automaton
[edit]The concept of 2DFAs was in 1997 generalized to quantum computing by John Watrous's "On the Power of 2-Way Quantum Finite State Automata", in which he demonstrates that these machines can recognize nonregular languages and so are more powerful than DFAs. [10]
Two-way pushdown automaton
[edit]A pushdown automaton that is allowed to move either way on its input tape is called two-way pushdown automaton (2PDA);[11] it has been studied by Hartmanis, Lewis, and Stearns (1965).[12] Aho, Hopcroft, Ullman (1968)[13] and Cook (1971)[14] characterized the class of languages recognizable by deterministic (2DPDA) and non-deterministic (2NPDA) two-way pushdown automata; Gray, Harrison, and Ibarra (1967) investigated the closure properties of these languages.[15]
References
[edit]- ^ Rabin, Michael O.; Scott, Dana (1959). "Finite automata and their decision problems". IBM Journal of Research and Development. 3 (2): 114–125. doi:10.1147/rd.32.0114.
- ^ This definition has been taken from lecture notes of CS682 (Theory of Computation) by Dexter Kozen of Stanford University
- ^ Kapoutsis, Christos (2005). "Removing Bidirectionality from Nondeterministic Finite Automata". In J. Jedrzejowicz, A.Szepietowski (ed.). Mathematical Foundations of Computer Science. MFCS 2005. Vol. 3618. Springer. pp. 544–555. doi:10.1007/11549345_47.
- ^ Ladner, Richard E.; Lipton, Richard J.; Stockmeyer, Larry J. (1984). "Alternating Pushdown and Stack Automata". SIAM Journal on Computing. 13 (1): 135–155. doi:10.1137/0213010. ISSN 0097-5397.
- ^ Geffert, Viliam; Okhotin, Alexander (2014). "Transforming Two-Way Alternating Finite Automata to One-Way Nondeterministic Automata". Mathematical Foundations of Computer Science 2014. Lecture Notes in Computer Science. Vol. 8634. pp. 291–302. doi:10.1007/978-3-662-44522-8_25. ISBN 978-3-662-44521-1. ISSN 0302-9743.
- ^ Sakoda, William J.; Sipser, Michael (1978). Nondeterminism and the Size of Two Way Finite Automata. STOC 1978. ACM. pp. 275–286. doi:10.1145/800133.804357.
- ^ Berman, Piotr; Lingas, Andrzej (1977). On the complexity of regular languages in terms of finite automata. Vol. Report 304. Polish Academy of Sciences.
- ^ Kapoutsis, Christos A. (2014). "Two-Way Automata Versus Logarithmic Space". Theory of Computing Systems. 55 (2): 421–447. doi:10.1007/s00224-013-9465-0.
- ^ Sipser, Michael (1980). "Lower Bounds on the Size of Sweeping Automata". Journal of Computer and System Sciences. 21 (2): 195–202. doi:10.1016/0022-0000(80)90034-3.
- ^ John Watrous. On the Power of 2-Way Quantum Finite State Automata. CS-TR-1997-1350. 1997. pdf
- ^ John E. Hopcroft; Jeffrey D. Ullman (1979). Introduction to Automata Theory, Languages, and Computation. Addison-Wesley. ISBN 978-0-201-02988-8. Here: p.124; this paragraph is omitted in the 2003 edition.
- ^ J. Hartmanis; P.M. Lewis II, R.E. Stearns (1965). "Hierarchies of Memory Limited Computations". Proc. 6th Ann. IEEE Symp. on Switching Circuit Theory and Logical Design. pp. 179–190.
- ^ Alfred V. Aho; John E. Hopcroft; Jeffrey D. Ullman (1968). "Time and Tape Complexity of Pushdown Automaton Languages". Information and Control. 13 (3): 186–206. doi:10.1016/s0019-9958(68)91087-5.
- ^ S.A. Cook (1971). "Linear Time Simulation of Deterministic Two-Way Pushdown Automata". Proc. IFIP Congress. North Holland. pp. 75–80.
- ^ Jim Gray; Michael A. Harrison; Oscar H. Ibarra (1967). "Two-Way Pushdown Automata". Information and Control. 11 (1–2): 30–70. doi:10.1016/s0019-9958(67)90369-5.