資料來源 : pyDict

[自]圖靈機(指計算自動化的一種數學理想化機器)

資料來源 : WordNet®

Turing machine
     n : a hypothetical computer with an infinitely long memory tape

資料來源 : Free On-Line Dictionary of Computing

Turing Machine
     
         A hypothetical machine defined in 1935-6 by
        {Alan Turing} and used for {computability theory} proofs.  It
        consists of an infinitely long "tape" with symbols (chosen
        from some {finite set}) written at regular intervals.  A
        pointer marks the current position and the machine is in one
        of a finite set of "internal states".  At each step the
        machine reads the symbol at the current position on the tape.
        For each combination of current state and symbol read, a
        program specifies the new state and either a symbol to write
        to the tape or a direction to move the pointer (left or right)
        or to halt.
     
        In an alternative scheme, the machine writes a symbol to the
        tape *and* moves at each step.  This can be encoded as a write
        state followed by a move state for the write-or-move machine.
        If the write-and-move machine is also given a distance to move
        then it can emulate an write-or-move program by using states
        with a distance of zero.  A further variation is whether
        halting is an action like writing or moving or whether it is a
        special state.
     
        [What was Turing's original definition?]
     
        Without loss of generality, the symbol set can be limited to
        just "0" and "1" and the machine can be restricted to start on
        the leftmost 1 of the leftmost string of 1s with strings of 1s
        being separated by a single 0.  The tape may be infinite in
        one direction only, with the understanding that the machine
        will halt if it tries to move off the other end.
     
        All computer {instruction set}s, {high level language}s and
        computer architectures, including {parallel processor}s, can
        be shown to be equivalent to a Turing Machine and thus
        equivalent to each other in the sense that any problem that
        one can solve, any other can solve given sufficient time and
        memory.
     
        Turing generalised the idea of the Turing Machine to a
        "Universal Turing Machine" which was programmed to read
        instructions, as well as data, off the tape, thus giving rise
        to the idea of a general-purpose programmable computing
        device.  This idea still exists in modern computer design with
        low level {microcode} which directs the reading and decoding
        of higher level {machine code} instructions.
     
        A {busy beaver} is one kind of Turing Machine program.
     
        Dr. Hava Siegelmann of {Technion} reported in Science of 28
        Apr 1995 that she has found a mathematically rigorous class of
        machines, based on ideas from {chaos} theory and {neural
        network}s, that are more powerful than Turing Machines.  Sir
        Roger Penrose of {Oxford University} has argued that the brain
        can compute things that a Turing Machine cannot, which would
        mean that it would be impossible to create {artificial
        intelligence}.  Dr. Siegelmann's work suggests that this is
        true only for conventional computers and may not cover {neural
        network}s.
     
        See also {Turing tar-pit}, {finite state machine}.
     
        (1995-05-10)