Turing machines with access to history

Lie-Access Neural Turing Machines

External neural memory structures have recently become a popular tool for algorithmic deep learning (Graves et al., 2014; Weston et al., 2014). These models generally utilize differentiable versions of traditional discrete memory-access structures (random access, stacks, tapes) to provide the storage necessary for computational tasks. In this work, we argue that these neural memory systems lack...

Turing Tests with Turing Machines

Comparative tests work by finding the difference (or the absence of difference) between a reference subject and an evaluee. The Turing Test, in its standard interpretation, takes (a subset of) the human species as a reference. Motivated by recent findings and developments in the area of machine intelligence evaluation, we discuss what it would be like to have a Turing Test where the reference a...

Fast Simulation of Turing Machines by Random Access Machines

Introduction to Turing Machines

A Turing machine can be viewed as a simple kind of computer, whose operations are constrainted to reading and writing symbols on a tape, or moving along the tape to the left or right. In theory, one has proven that the computability of Turing machines is equivalent to recursive functions. This article defines and verifies the Turing machines of summation and three primitive functions which are ...

Some improvements in fuzzy turing machines

In this paper, we improve some previous definitions of fuzzy-type Turing machines to obtain degrees of accepting and rejecting in a computational manner. We apply a BFS-based search method and some level’s upper bounds to propose a computational process in calculating degrees of accepting and rejecting. Next, we introduce the class of Extended Fuzzy Turing Machines equipped with indeterminacy s...