Workshop on Model Theoretic Algebra and Algebraic
Methods of Computation 4 - 14 SeptemberOrganisers:
Felipe Cucker (Hong Kong), Pascal Koiran (Lyon), Angus
Macintyre (Edinburgh), Christian Michaux (Mons)
Supported
by: The Engineering and Physical Sciences Research Council
The
objective of the Workshop was to bring together several research groups
concerned with definability in classical algebraic structures. There are three
easily identified groups:
- (i) applied model theorists;
- (ii) the group centred round BlumShub and Smale
concerned with computability on general structures;
- (iii) the Russian school of algorithmic geometry.
One motivation for holding the Workshop was that there had
begun to be significant movement between the groups (e.g. interactions between
Macintyre of group (i) with Koiran from group (ii), and with Grigoriev from
group (iii)). The algorithmic issues, especially for group (ii), are
inextricably linked with definability issues, where model theorists have long
experience and a repertoire of techniques. The success of the meeting owed much
to the fact that the main groups were strongly represented, and brought to
Edinburgh ideas which were evolving even as the meeting was planned.
The meeting resulted in progress in four particular areas:
1.
Geometry Since Khovanskis paper in 1980, on the uniform
finiteness of number of connected components for semi-Pfaffian sets, there has
been intensive activity on related algorithmic and definability issues. On the
pure side, the major work is due to Wilkie, in his proofs of model-completeness
for real exponentiation and o-minimality of Pfaffian functions. By general
model theory this yields deep results on Whitney stratifications. A major
challenge is to effectivize the results, because of potential relevance to
neural networks, sparse polynomials, etc. During the meeting Vorobjov reported
on joint work with the analytic geometer Gabrielov, in which reasonably
effective upper bounds are obtained. This should encourage model theorists to
take up again the issue of a more explicit decidability proof for real
exponentiation.
A quite startling advance was reported by Rojas,
concerning connected components of sets defined by trinomials. Here one has
been able to get close to optimal bounds, in contrast to the astronomical
bounds got by naive use of Hovanskis method.
In the setting of
complex algebraic geometry Chistov explained some basic new algorithms for
smooth stratification.
2. VC dimension and learning theory
Several years ago Karpinski and Macintyre had shown the power of a
combination of Khovanskis methods and model theory by getting close to
the optimal bounds for the VC-dimension of sigmoidal neural networks. More
generally they had begun to link Vapniks more recent work to
o-mimimality, and related model-theoretic notions, with a view to randomized
algorithms in certain real and p-adic geometrical situations. Macintyre had
been unaware that the interests of Smales group had also turned in this
direction. One of the highlights of the meeting was Smales account of his
project, mainly with Cucker, to bring deep functional analysis to bear on the
estimation problems (sample error, approximation error) of a suitably abstract
learning theory. It is not at all clear how this approach relates to that via
o-minimality and Morse theory. The Workshop certainly accelerated discussion of
this basic issue.
3. Database theory In recent years some
highly original work of Baldwin, Benedikt et al. has shown the importance of
modern model-theoretic notions for database theory. Benedikts lecture on
this led to an interaction with Macintyre, concerning p-adic aspects of this.
The literature until now deals with real geometrical situations where the
relevance of VC-dimensions can be well-estimated. In the p-adic cases, the
VC-dimensions are known to be finite, but one does not yet know how to
calculate them.
4. Circuit complexity and model theory
Krajicek reported on deep work joint with Scanlon, on model-theoretic Euler
characteristics and their connections to the hardcore complexity issues around
the Hilbert Nullstellensatz (a favourite theme of the Smale school also).
As it turned out, the most striking presentations all had to do with
algorithms and geometry (broadly construed). Any new algorithm is likely to be
of use somewhere in engineering, computer science or artificial intelligence.
Model theory has already made significant contributions to learning theory, and
the new involvement of Smales group, with a different perspective, should
consolidate the link.
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List
Participants: Basarab, Serban, Romanian Academy of
Sciences Benedikt, Michael, Bell Labs Blum, Lenore, Carnegie Mellon
University Borovik, Alexandre, UMIST Bradfield, Julian, University of
Edinburgh Buergisser, Peter, University of Paderborn Chapuis, Olivier,
Université Lyon I Chistov, Aleksandr L, Russian Academy of Sciences
Cucker, Felipe, City University of Hong Kong de Naurois, Paulin, Ecole
Normale Superieure de Lyon Dickmann, Max, University Paris VII
Fournier, Hervé, ENS Lyon Grigorev, Dimitri, Université
de Rennes 1 Kalorkoti, Kyriakos, Unviersity of Edinburgh Karpinski,
Marek, Universität Bonn Koiran, Pascal, ENS Lyon Krajicek, Jan,
Academy of Sciences at Prague Langley, Simon, University of the West of
England MacIntyre, Angus, University of Edinburgh Makowsky, Johann,
Technion - Israel Institute of Technology Marker, David, University of
Illinois at Chicago Meer, Klaus, Odense University Michaux, Christian,
Université de Mons-Hainaut Petrovich, Alejandro, University of
Buenos Aries Poizat, Bruno, Université Claude Bernard (Lyon 1)
Portier, Natacha, ENS Lyon Prunescu, Mihai, Universität Greifswald
Richardson, Dan, University of Bath Rojas, J Maurice, City University
of Hong Kong Shackell, John, University of Kent at Canterbury Smale,
Stephen, City University of Hong Kong Stevens, Perdita, University of
Edinburgh Toffalori, Carlo, University of Camerino Tucker, J V,
University of Wales, Swansea Vorobjov, Nicolai, University of Bath
Xirotiri, Olga, University of Crete
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