4,560 research outputs found
Adaptable processes
We propose the concept of adaptable processes as a way of overcoming the
limitations that process calculi have for describing patterns of dynamic
process evolution. Such patterns rely on direct ways of controlling the
behavior and location of running processes, and so they are at the heart of the
adaptation capabilities present in many modern concurrent systems. Adaptable
processes have a location and are sensible to actions of dynamic update at
runtime; this allows to express a wide range of evolvability patterns for
concurrent processes. We introduce a core calculus of adaptable processes and
propose two verification problems for them: bounded and eventual adaptation.
While the former ensures that the number of consecutive erroneous states that
can be traversed during a computation is bound by some given number k, the
latter ensures that if the system enters into a state with errors then a state
without errors will be eventually reached. We study the (un)decidability of
these two problems in several variants of the calculus, which result from
considering dynamic and static topologies of adaptable processes as well as
different evolvability patterns. Rather than a specification language, our
calculus intends to be a basis for investigating the fundamental properties of
evolvable processes and for developing richer languages with evolvability
capabilities
On the possible Computational Power of the Human Mind
The aim of this paper is to address the question: Can an artificial neural
network (ANN) model be used as a possible characterization of the power of the
human mind? We will discuss what might be the relationship between such a model
and its natural counterpart. A possible characterization of the different power
capabilities of the mind is suggested in terms of the information contained (in
its computational complexity) or achievable by it. Such characterization takes
advantage of recent results based on natural neural networks (NNN) and the
computational power of arbitrary artificial neural networks (ANN). The possible
acceptance of neural networks as the model of the human mind's operation makes
the aforementioned quite relevant.Comment: Complexity, Science and Society Conference, 2005, University of
Liverpool, UK. 23 page
The Algebraic View of Computation
We argue that computation is an abstract algebraic concept, and a computer is
a result of a morphism (a structure preserving map) from a finite universal
semigroup.Comment: 13 pages, final version will be published elsewher
Multi-Head Finite Automata: Characterizations, Concepts and Open Problems
Multi-head finite automata were introduced in (Rabin, 1964) and (Rosenberg,
1966). Since that time, a vast literature on computational and descriptional
complexity issues on multi-head finite automata documenting the importance of
these devices has been developed. Although multi-head finite automata are a
simple concept, their computational behavior can be already very complex and
leads to undecidable or even non-semi-decidable problems on these devices such
as, for example, emptiness, finiteness, universality, equivalence, etc. These
strong negative results trigger the study of subclasses and alternative
characterizations of multi-head finite automata for a better understanding of
the nature of non-recursive trade-offs and, thus, the borderline between
decidable and undecidable problems. In the present paper, we tour a fragment of
this literature
Comparing hierarchies of total functionals
In this paper we consider two hierarchies of hereditarily total and
continuous functionals over the reals based on one extensional and one
intensional representation of real numbers, and we discuss under which
asumptions these hierarchies coincide. This coincidense problem is equivalent
to a statement about the topology of the Kleene-Kreisel continuous functionals.
As a tool of independent interest, we show that the Kleene-Kreisel functionals
may be embedded into both these hierarchies.Comment: 28 page
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