Call for papers
Machine Learning as Experimental Philosophy of Science
Machine learning studies inductive strategies in algorithms. The philosophy of science investigates inductive strategies as they appear in scientific practice. Although the two disciplines have developed largely independently, they share many of the same issues. This is slowly coming to be recognized, as evidenced in the annual Uncertainty in AI and AI and Statistics conferences. This workshop will explore the extent to which the methods and resources of philosophy of science and machine learning can inform one another.
In Computational Philosophy of Science (1988) Paul Thagard presented a challenge to the philosophical community: philosophical theories of scientific method, if they are worth their salt, should be implementable as computer programs. In this workshop we will address this challenge and also the inverse challenge to machine learning researchers: both machine learning algorithms and methods for evaluating machine learning algorithms should be implementations of sensible approaches to philosophy of science. Machine learning researchers have only recently discovered the relevance of statistics and philosophical views on the foundations of statistics to evaluating the performance of their systems; we hope this workshop will carry that discussion further.
The workshop will therefore focus on such questions as:
How accounts of confirmation, explanation, discovery and theoretical unification developed in the philosophy of science area can be used to develop automatic learning systems?
This workshop is one of a number of workshops jointly sponsored by the
European Conference on Machine Learning (ECML'01) 5th European
Conference on Principles and Practice of Knowledge Discovery in
Databases (PKDD'01). Have a look at their workshop
Accepted papers will be published in the first instance as workshop
notes and on the web. Authors are invited to revise their articles in
the light of the discussions at the workshop and submit them to a
special issue we have arranged with the Journal for Experimental and Theoretical
8 June 2001
25 June 2001
13 July 2001
3 Sept 2001
We prefer papers to be submitted electronically in a postscript email
attachment to both organizers simultaneously (i.e., to email@example.com
Only if strictly necessary, submissions may be sent alternatively as
an MS Word attachment. A last resort would be to mail or fax
submissions to the address below.
c/o Kevin B. Korb
School of Computer Science
Clayton, VIC 3800
Fax: +61 (03) 9905-5146
(Monash University, Australia)
Hilan Bensusan (Bristol University, UK)