Publications of A. J. Bagnall
The
Official Database is probably more up to date (but less accurate!)
Journal Papers
A. J. Bagnall, C. Ratanamahatana, E. Keogh, S. Lonardi and G. J. Janacek,
A bit level representation for time series data mining with shape based
similarity , Mining and Knowledge Discovery Journal, Published online: 12 May 2006
PDF
A. J. Bagnall and I. Toft, Autonomous Adaptive Agents for Single Seller
Sealed Bid Auctions, Journal of Autonomous Agents and Multi-Agent Systems,
Vol 12, Issue 3, Pages: 259 - 292, May 2006 PDF
A. J. Bagnall and G. D. Smith, A Multi-Agent Model of the UK Market in
Electricity Generation , IEEE Transactions on Evolutionary Computation,
9(5), October 2005 PDF
A. J. Bagnall and G.A. Janacek, Clustering Time Series with Clipped
Data, Machine Learning, vol 58(2) p. 151-178 (2005) PDF
A. J. Bagnall, V. J. Rayward-Smith and I. M. Whittley, (2001), The Next
Release Problem, Information and Software Technology, Vol. 43, 14, p.
883-890
Conference Papers
I.M. Whittley, A.J. Bagnall, L. Bull, M. Pettipher, M. Studley and F. Tekiner Attribute Selection Methods for Filtered Attribute Subspace based Bagging with Injected Randomness (FASBIR), In Feature Selection for Data Mining Workshop, Part of the 2006 SIAM Conference on Data Mining, 2006.
Z. Zatucchna and Bagnall, A.J., A Reinforcement Learning Agent with Associative Perception, In Symposium on Associative Learning and Reinforcement Learning at Adaptation in Artificial and Biological Systems, 2006.
Z. Zatucchna and Bagnall, A.J., Modelling of Temperament in an Associative Reinforcement Learning , In Symposium on Associative Learning and Reinforcement Learning at Adaptation in Artificial and Biological Systems, 2006
Z. Zatucchna and A. J. Bagnall, AgentP Classifier System: Self-adjusting
vs. Gradual Approach Proceedings of the 2005 Congress on Evolutionary
Computation
Z. Bull, M. Studley, A. J. Bagnall and I. Whittley, On the use of Rule
Sharing in Learning Classifier System Ensembles h Proceedings of the 2005
Congress on Evolutionary Computation
A. J. Bagnall and G.A. Janacek, A Likelihood Ratio distance Measure for
the Similarity between the Fourier Transform of Time Series accepted for the
Ninth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-05)
PDF
C. Ratanamahatana, E. Keogh, A. J. Bagnall, S. Lonardi. A Novel Bit Level
Time Series Representation with Implication of Similarity Search and Clustering
Accepted for the Ninth Pacific-Asia Conference on Knowledge Discovery and
Data Mining (PAKDD-05) Word Doc
A. J. Bagnall and Z. Zatuchna, On the Classification of Maze Problems
, Bull, L. & Kovacs, T. (eds) (2005) Foundations of Learning Classifier
Systems, Lecture Notes in Artificial Intelligence. Springer
A. J. Bagnall and I. Toft Zero Intelligence Plus and Gjerstad-Dickhaut
Agents for Sealed Bid Auctions, Workshop on Trading Agent Design and
Analysis, part of the Third Internationmal Conference on Autonomous Agents and
Multi-Agent Systems (AAMAS 2004),New York, USA, 19th-23rd July, 2004, pages
59-64 PDF
A. J. Bagnall and G. Janakec Clustering Time Series from ARMA Models with
Clipped Data, Proceedings of the International Conference on Knowledge
Discovery in Data and Data Mining (ACM SIGKDD 2004), Seattle, USA, 22nd-25th
August, 2004, pages 49-58 PDF
A.A. Gill, G. D. Smith and A. J. Bagnall Improving decision tree
performance through induction and cluster-based stratified sampling,
Proceedings of Fifth International Conference on Intelligent Data Engineering
and Automated Learning (IDEAL'04)), 2004,
A. J. Bagnall and G. Janakec Clustering Time Series from ARMA Models with
Clipped Data, Technical Report CMP-C04-01, School of Computing Sciences,
University of East Anglia, February 2004. PDF
A. J. Bagnall, G. Janakec, B. de la Iglesia and M. Zhang Clustering Time
Series from Mixture Polynomial Models with Discretised Data, Proceedings of
the second Australasian Data Mining Workshop, December 2003. PDF
A. J. Bagnall, G. Janakec, B. de la Iglesia and M. Zhang Clustering Time
Series from Mixture Polynomial Models with Discretised Data, Technical
Report CMP-C03-17, School of Computing Sciences, University of East Anglia,
September 2003. PDF
A. J. Bagnall and I. Toft An Agent Model for First Price and Second Price
Private Value Auctions , in Proceedings of the 6th International Conference
on Artificial Evolution, 2003 PDF
A. J. Bagnall and G. C. Cawley Learning classifier systems for data
mining : A comparison of XCS with other classifiers for the Forest Cover
dataset,In Proceedings of the IEEE/INNS International Joint Conference on
Artificial Neural Networks (IJCNN-2003), Portland, Oregon, USA, 20th-24th July,
2003.
compressed postscript , PDF
A. J. Bagnall Modelling the UK market in electricity generation with
autonomous adaptive agents PhD thesis, September 2000. compressed
postscript , PDF
A. J. Bagnall and G. D. Smith, Game playing with autonomous adaptive
agents in a simplified economic model of the UK market in electricity
generation In Proceedings of IEEE-PES / CSEE International Conference on
Power System Technology (Powercon 2000), Perth, Australia, 1st-5th December,
2000. compressed
postscript, PDF
A. J. Bagnall, A Multi-Adaptive Agent Model of Generator Bidding in the
UK Market in Electricity, In Proceedings of the AAAI Genetic and
Evolutionary Computation Conference (GECCO-2000), pages 605-612, 2000, Morgan
Kaufmann: San Francisco, CA,
compressed
postscript , PDF
A. J. Bagnall and G. D. Smith, An Adaptive Agent Model for Generator
Company Bidding in the UK Power Pool , Lecture Notes in Computer Science
1829, pages 191-203, 1999
postscript , compressed
postscript , PDF
A. J. Bagnall and G. D. Smith, Using an Adaptive Agent to Bid in a
Simplified Model of the UK Market in Electricity , Proceedings of Genetic
and Evolutionary Computation Conference, 1999
postscript
A. J. Bagnall, G. P. McKeown and V. J. Rayward-Smith, ,Cryptanalysis of a
Three Rotor Machine Using a Genetic Algorithm,Proceedings of the Seventh
International Conference on Genetic Algorithms,1997
compressed
postscript , PDF
A. J. Bagnall, The Applications of Genetic Algorithms in Cryptanalysis
Masters Thesis
compressed
postscript , PDF