The ZULU Competition
Supported by Pascal 2 Network of Excellence
Zulu is an active learning competition, where participants are to build
algorithms that can learn deterministic finite automata (DFA) by making
the smallest number of membership queries to the server/oracle.
As a web platform ( http://labh-curien.univ-st-etienne.fr/zulu/ ), Zulu
allows users to generate tasks, to interact with the Oracle in learning
sessions and to record the results of the users.
The users are provided with:
- a baseline algorithm written in JAVA and/or
- the elements allowing to build from scratch a new learning algorithm
capable of interacting with the server.
The baseline is a variation of Algorithm L* with some sampling done to
simulate equivalence queries. As a starting point, the users can therefore
play with some simple JAVA code, and easily explore all aspects of Zulu.
- Now: Zulu platform is open, anyone may register, develop and test
- June 1st: Official beginning of the competition
- June 30th: Deadline for scoring, submissions closed
- July 7th: Notifications of the results
- July 15th: Deadline for submission of abstracts to the workshop
- September 13-16th: workshop at ICGI (in Valencia, Spain, September
13-16, 2010, http://users.dsic.upv.es/workshops/icgi2010/ )
Prizes and publications:
The winner of the Zulu competition will receive a prize of 1000.
Participants are encouraged to present their innovations as extended
abstracts to the Zulu workshop that will be organised during ICGI. A
journal special issue will also be considered.
- Dana Angluin, Yale University, USA
- Leo Becerra Bonache, Universidad de Tarragona, Spain
- François Coste, IRISA, Rennes, France
- Alex Clark, Royal Holloway University of London, UK
- Ricard Gavalda, Universidad Politecnica de Barcelona, Spain
- Colin de la Higuera, University of Nantes, France
- Jean-Christophe Janodet, University of Saint-Etienne, France
- Aurelien Lemay, University of Lille, France
- Laurent Miclet, ENSAT Lannion and IRISA, France
- Tim Oates, University of Maryland, USA
- Anssi Yli Jyra, University of Helsinki, Finland
- Menno van Zaanen, Tilburg University, The Netherlands
In a number of learning application fields, including computational
linguistics, user modelling, web services, robotics, pattern recognition,
standard learning techniques usually make use of huge corpora that are not
One possible way around this problem is to interrogate an expert with a
number of chosen queries, in an interactive mode, until a satisfying model
is reached. In this case, an important indicator of success is the amount
of energy the expert has spent in order for learning to be successful. A
nice learning paradigm covering this situation is that of Query Learning,
introduced by Dana Angluin.
In the field of Grammatical Inference, Query Learning was thoroughly
investigated to learn deterministic finite automata (DFA). As negative
results, it was proved that DFA could not be learned from just a
polynomial number of membership queries nor from just a polynomial number
of strong equivalence queries. On the other hand, algorithm L* designed by
Angluin, was proved to learn DFA from a polynomial number of both
membership and equivalence queries.
These results yield several successful applications in Robotics, Games and
Agents Technologies, Information Retrieval, Hardware and Software
In Zulu, the goal is to optimise the learning by trying to minimize the
number of queries for a given task.
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