“We pay too much attention to the details of algorithms. [...] We must begin to subordinate the engineering to the philosophy.”
John Hartigan (1996)

Motivations and goals
The fields of pattern recognition and machine learning can arguably be considered as a modern-day incarnation of an endeavor which has challenged mankind since antiquity. Indeed, fundamental questions pertaining to categorization, abstraction, generalization, induction, etc., have been on the agenda of mainstream philosophy, under different names and guises, since its inception and, with the advent of modern digital computers and the availablity of enormous amount of raw data, these questions have now taken a computational flavor. As it often happens with scientific research, in the early days of pattern recognition there used to be a genuine interest around philosophical and conceptual issues, but over time the interest shifted almost entirely to technical and algorithmic aspects, and became driven mainly by practical applications. With this reality in mind, it is instructive to remark that although the dismissal of philosophical inquiry at times of intense incremental scientific progress is understandable to allow time for the immediate needs of problem-solving, it is also sometimes responsible for preventing or delaying the emergence of true scientific progress.

In recent years there has been a revival of interest around the foundational and/or philosophical problems of pattern recognition and machine learning, from both the computer scientist’s and the philosopher’s camps. This suggests that the time is ripe to attempt establishing a long-term dialogue between the philosophy and the pattern recognition/machine learning communities with a view to foster cross-fertilization of ideas. In particular, we do feel that the present moment is appropriate for reflection, reassessment and eventually some synthesis, with the aim of providing the fields a self-portrait of where it currently stands and where it is going as a whole, hopefully suggesting new directions.

The goal of this special issue is precisely to consolidate research efforts in this area, and to provide a timely and coherent picture of the state of the art in the field. Accordingly, topics of interest will include (but are not limited to):

connections to epistemology and philosophy of science (inductionism, falsificationism, etc.)
essentialism vs. anti-essentialism (e.g., feature-based vs similarity/relational approaches)
foundations of probability and causality (Bayesianism, etc.)
abstraction and generalization
connections to decision and game theory
similarity and categorization
the nature of pattern recognition research
the nature of information
ethical issues

Important dates

Submission deadline: July 1, 2014
First reviews: December 2014
Revised papers: February 2015
Second reviews/decisions: April 2015

Guest editor
Marcello Pelillo
Ca’ Foscari University, Venice, Italy
pelillo@dsi.unive.it

Paper submission

Prepare your paper following the journal’s guidelines, which include specifications for special issue submissions.
Submit the manuscript online via the Pattern Recognition Letters website (http://ees.elsevier.com/patrec), selecting the following special issue identifier: PhilPR.
Send an e-mail to M. Pelillo (pelillo@dsi.unive.it), with subject “PRL special issue submission” to notify the editor of your submission.