79 research outputs found
Synchronous Online Philosophy Courses: An Experiment in Progress
There are two main ways to teach a course online: synchronously or asynchronously. In an asynchronous course, students can log on at their convenience and do the course work. In a synchronous course, there is a requirement that all students be online at specific times, to allow for a shared course environment. In this article, the author discusses the strengths and weaknesses of synchronous online learning for the teaching of undergraduate philosophy courses. The author discusses specific strategies and technologies he uses in the teaching of online philosophy courses. In particular, the author discusses how he uses videoconferencing to create a classroom-like environment in an online class
Effective Physical Processes and Active Information in Quantum Computing
The recent debate on hypercomputation has arisen new questions both on the
computational abilities of quantum systems and the Church-Turing Thesis role in
Physics. We propose here the idea of "effective physical process" as the
essentially physical notion of computation. By using the Bohm and Hiley active
information concept we analyze the differences between the standard form
(quantum gates) and the non-standard one (adiabatic and morphogenetic) of
Quantum Computing, and we point out how its Super-Turing potentialities derive
from an incomputable information source in accordance with Bell's constraints.
On condition that we give up the formal concept of "universality", the
possibility to realize quantum oracles is reachable. In this way computation is
led back to the logic of physical world.Comment: 10 pages; Added references for sections 2 and
Is there any real substance to the claims for a 'new computationalism'?
'Computationalism' is a relatively vague term used to describe attempts to apply Turing's model of computation to phenomena outside its original purview: in modelling the human mind, in physics, mathematics, etc. Early versions of computationalism faced strong objections from many (and varied) quarters, from philosophers to practitioners of the aforementioned disciplines. Here we will not address the fundamental question of whether computational models are appropriate for describing some or all of the wide range of processes that they have been applied to, but will focus instead on whether `renovated' versions of the \textit{new computationalism} shed any new light on or resolve previous tensions between proponents and skeptics. We find this, however, not to be the case, because the 'new computationalism' falls short by using limited versions of "traditional computation", or proposing computational models that easily fall within the scope of Turing's original model, or else proffering versions of hypercomputation with its many pitfalls
Philosophy of Computer Science: An Introductory Course
There are many branches of philosophy called “the philosophy of X,” where X = disciplines ranging from history to physics. The philosophy of artificial intelligence has a long history, and there are many courses and texts with that title. Surprisingly, the philosophy of computer science is not nearly as well-developed. This article proposes topics that might constitute the philosophy of computer science and describes a course covering those topics, along with suggested readings and assignments
Solomonoff Induction: A Solution to the Problem of the Priors?
In this essay, I investigate whether Solomonoff’s prior can be used to solve the problem of the priors for Bayesianism. In outline, the idea is to give higher prior probability to hypotheses that are "simpler", where simplicity is given a precise formal definition. I begin with a review of Bayesianism, including a survey of past proposed solutions of the problem of the priors. I then introduce the formal framework of Solomonoff induction, and go through some of its properties, before finally turning to some applications. After this, I discuss several potential problems for the framework. Among these are the fact that Solomonoff’s prior is incomputable, that the prior is highly dependent on the choice of a universal Turing machine to use in the definition, and the fact that it assumes that the hypotheses under consideration are computable. I also discuss whether a bias toward simplicity can be justified. I argue that there are two main considerations favoring Solomonoff’s prior: (i) it allows us to assign strictly positive probability to every hypothesis in a countably infinite set in a non-arbitrary way, and (ii) it minimizes the number of "retractions" and "errors" in the worst case
Positive Affirmation of Non-Algorithmic Information Processing
One of the most compelling problems in science consists in understanding how
living systems process information. After all, the way they process information
defines their capacities to learning and adaptation. There is an increasing
consensus in that living systems are not machines in any sense. Biological
hyper-computation is the concept coined that expresses that living beings
process information non-algorithmically. Maldonado and Gomez (2015) have
brought up biological hyper-computation as a new problem within complexity
science. This paper aims at proving a positive understanding of non-algorithmic
processes. A number of arguments are brought that support the claim. This
fosters, it is argued, a brand new understanding of information processing
among living beings. Some conclusions are drawn at the end.Comment: 9 pages, 1 tabl
The Complexification of Engineering
This paper deals with the arrow of complexification of engineering. We claim
that the complexification of engineering consists in (a) that shift throughout
which engineering becomes a science; thus it ceases to be a (mere) praxis or
profession; (b) becoming a science, engineering can be considered as one of the
sciences of complexity. In reality, the complexification of engineering is the
process by which engineering can be studied, achieved and understood in terms
of knowledge, and not of goods and services any longer. Complex engineered
systems and bio-inspired engineering are so far the two expressions of a
complex engineering.Comment: 9 pages, 1 figure, 1 table, preprint; Complexity. In the print (2011
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