This paper describes the instantiation of a type of Learning Automata (LA) that is all but unknown. Derived from the later theories of Alan Turing the LA is a dynamic, artifactual model of natural intelligence that uses cybernetic theory to derive machine intelligence. Similarly, the bibliographic references cited here may be unknown to readers unfamiliar with this branch of self-organizing (cy...

Finite-state transducers are simple theoretical machines that are useful in expressing easilycomputable functions and relations. This investigation considers the relations formed when transducers are iterated arbitrarily many times, a construction which is useful in model checking. In particular, we consider a number of decision problems over various classes of transducers, and attempt to deter...

In this paper we modify some previous definitions of fuzzy Turing machines to define the notions of accepting and rejecting degrees of inputs, computationally. We use a BFS-based search method and obtain an upper level bound to guarantee the existence of accepting and rejecting degrees. We show that fuzzy, generalized fuzzy and classical Turing machines have the same computational power. Next, ...

This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define so...

Wolfram [2, p. 707] and Cook [1, p. 3] claim to prove that a (2,5) Turing machine (2 states, 5 symbols) is universal, via a universal cellular automaton known as Rule 110. The first part of this paper points out a critical gap in their argument. The second part bridges the gap, thereby giving what appears to be the first proof of universality. 1 The claim Wolfram [2, p. 707] and Cook [1, p. 3] ...

In this paper, the problem of applying changes to software at runtime is considered. The computability theory is used in order to develop a more general and programming-language-independent model of computation with support for runtime changes. Various types of runtime changes were defined in terms of computable functions and Turing machines. The properties of such functions and machines were u...

The architecture of neural Turing machines is differentiable end to end and is trainable with gradient descent methods. Due to their large unfolded depth Neural Turing Machines are hard to train and because of their linear access of complete memory they do not scale. Other architectures have been studied to overcome these difficulties. In this report we focus on improving the quality of predict...

The discovery that some Turing Machines are universal computers that can emulate any other Turing Machine, and thus, according to the Church-Turing thesis, any effective computational procedure available to the human mind, led to the development of a powerful theory of the complexity of individual objects in the work of Solomonoff, Kolmogorov and Chaitin. Intuitively this theory identifies the ...

In this paper we sketch an ACL2-checked proof that a simple but unbounded Von Neumann machine model is Turing Complete, i.e., can do anything a Turing machine can do. The project formally revisits the roots of computer science. It requires re-familiarizing oneself with the definitive model of computation from the 1930s, dealing with a simple “modern” machine model, thinking carefully about the ...

A Thermodynamic Turing Machine (TTM) concept is introduced. A TTM is a classical computing paradigm where the natural laws of thermodynamics are exploited in the form of a discrete controlled and configurable classical Boltzmann gas to efficiently implement logical mathematical operations. In its most general form the machine consists of a set of configurable and switchable interlocking equi-el...