Publications by Tim Kovacs

This is a list of all publications (co-)authored by Tim Kovacs that are contained in the publications database of the Department of Computer Science, University of Bristol. To perform an alternative search of the publications database, please go to the publications database home page.

2012

• Tim Kovacs, A latex style file for conference booklets. , Department of Computer Science. September 2012. No electronic version available. External information
• Tim Kovacs, Genetics-based machine learning. Chapter in Handbook of Natural Computation. ISBN 978-3-540-92909-3. August 2012. PDF, 2242 Kbytes. External information
• GECCO '12: Proceedings of the fourteenth international conference on genetic and evolutionary computation. Terry Soule, et al., including, Tim Kovacs, (eds.). ACM. ISBN 978-1-4503-1177-9. July 2012. No electronic version available.

2011

• Tim Kovacs, Andy Wills, Generalization vs. Discrimination in Learning. Chapter in Encyclopedia of the Sciences of Learning. Norbert M. Seel, (eds.). November 2011. PDF, 269 Kbytes.
• Narayanan Edakunni, Tim Kovacs, Gavin Brown, Boosting as a Product of Experts. Uncertainty in Artificial Intelligence. Proceedings of the Twenty-Seventh Conference, pp. 187–194. July 2011. PDF, 307 Kbytes.
• James Marshall, Rafal Bogacz, Anna Dornhaus, Robert Planque, Tim Kovacs, Nigel R. Franks, On optimal decision making in brains and social insect colonies. Chapter in Modelling Natural Action Selection. Anil K. Seth, Tony J. Prescott, Joanna J. Bryson, (eds.). June 2011. No electronic version available. External information
• Narayanan Edakunni, Gavin Brown, Tim Kovacs, Online, GA based Mixture of Experts : a Probabilistic Model of UCS. Proceedings of the 2011 Conference on Genetic and Evolutionary Computation. ISBN 978-1-4503-0557-0, pp. 1267–1274. April 2011. PDF, 293 Kbytes.
• Tim Kovacs, Narayanan Edakunni, Gavin Brown, Accuracy Exponentiation in UCS and its Effect on Voting Margins. Proceedings of the 2011 Conference on Genetic and Evolutionary Computation. ISBN 978-1-4503-0557-0, pp. 1243–1250. April 2011. PDF, 505 Kbytes.
• Tim Kovacs, Robert Egginton, On the analysis and design of software for reinforcement learning, with a survey of existing systems. Machine Learning, 84(1--2), pp. 7–49. February 2011. No electronic version available. External information

2010

• Tim Kovacs, Elaboration on the policy improvement theorem for soft policies in reinforcement learning. CSTR-10-007, University of Bristol. October 2010. No electronic version available.
• Tim Kovacs, Robert Egginton, Software for Experiments. CSTR-10-006, University of Bristol. July 2010. PDF, 573 Kbytes.
• Ralph Pethica, Gary Barker, Tim Kovacs, Julian Gough, TreeVector: Scalable, Interactive, Phylogenetic Trees for the Web. PLoS ONE, 5(1). ISBN eISSN-1932-6203, pp. e8934–e8934. January 2010. PDF, 254 Kbytes.

2009

• James Marshall, Rafal Bogacz, Anna Dornhaus, Robert Planque, Tim Kovacs, Nigel Franks, On optimal decision-making in brains and social insect colonies. Journal of the Royal Society: Interface, 6, pp. 1065–1074. November 2009. No electronic version available. External information
• Narayanan Edakunni, Tim Kovacs, Gavin Brown, James Marshall, Modeling UCS as a Mixture of Experts. Proceedings of the 2009 Genetic and Evolutionary Computation Conference (GECCO'09). ISBN 978-1-60558-325-9 , pp. 1187–1194. July 2009. PDF, 226 Kbytes.
• Narayanan Edakunni, Tim Kovacs, Probabilistic Modeling of UCS : a theoretical study. CSTR-09-002, University of Bristol. April 2009. No electronic version available.
• Kamran Shafi, Tim Kovacs, Hussein A. Abbass, Weiping Zhu, Intrusion Detection with Evolutionary Learning Classifier Systems. Natural Computing, 8(1), pp. 3–27. March 2009. PDF, 618 Kbytes. External information

2008

• Tim Kovacs, Aims, Objectives and Guidelines for PhD students. CSTR-08-002, University of Bristol. November 2008. No electronic version available. External information
• Tim Kovacs, Artificial Intelligence through Search: Solving Sudoku Puzzles. CSTR-08-003, Department of Computer Science, University of Bristol. October 2008. PDF, 212 Kbytes.
• Learning Classifier Systems. 10th and 11th International Workshops (2006-2007). Jaume Bacardit, Ester Bernadó-Mansilla, Martin Butz, Tim Kovacs, Xavier Llorà, Keiki Takadama, (eds.). Springer. ISBN 978-3-540-88137-7. October 2008. No electronic version available. External information

2007

• Robert Planqué, Francois-Xavier Dechaume-Moncharmont, Nigel R. Franks, Tim Kovacs, James Marshall, Why do house-hunting ants recruit in both directions?. Naturwissenschaften, 94(11). ISSN 0028-1042, pp. 911–918. November 2007. PDF, 574 Kbytes. External information
• Proceedings of the 2007 Genetic and Evolutionary Compuation Conference (GECCO 2007). Dirk Thierens, Benjamin Doerr, Tim Kovacs, Sanjeev Kumar, Hans-Georg Beyer, Mauro Birattari, Josh Bongard, Jurgen Branke, John Andrew Clark, Dave Cliff, Clare Bates Congdon, Kalyanmoy Deb, (eds.). ACM Press. ISBN 978-1-59593-697-4. July 2007. No electronic version available.
• James Marshall, Gavin Brown, Tim Kovacs, Bayesian Estimation of Rule Accuracy in UCS. Proceedings of the 2007 GECCO Conference Companion on Genetic and Evolutionary Computation, pp. 2831–2834. July 2007. PDF, 112 Kbytes.
• Tim Kovacs, Larry Bull, Toward a better understanding of rule initialization and deletion. Workshop Proceedings of the Genetic and Evolutionary Computation Conference (GECCO). ISBN 978-1-59593-698-1, pp. 2777–2780. July 2007. PDF, 412 Kbytes. External information
• Gavin Brown, Tim Kovacs, James Marshall, UCSpv: principled voting in UCS rule populations. Proceedings of the 2007 Genetic and Evolutionary Computation Conference (GECCO 2007). ISBN 978-1-59593-697-4, pp. 1774–1781. July 2007. PDF, 428 Kbytes.
• Robert Egginton, Thomas Hinton, Tim Kovacs, Tobias Larsen, Some Observations on the General Problem of Sensor Planning. CSTR-07-011, University of Bristol. May 2007. PDF, 110 Kbytes.
• Learning Classifier Systems. International Workshops, IWLCS 2003-2005, Revised Selected Papers. Tim Kovacs, Xavier LLora, Keiki Takadama, Pier Luca Lanzi, Wolfgang Stolzmann, Stewart W. Wilson, (eds.). Springer. ISBN 3-540-71230-5. April 2007. No electronic version available. External information
• Robert Planqué, Anna Dornhaus, Nigel R. Franks, Tim Kovacs, James Marshall, Weighting waiting in collective decision-making. Behavioral Ecology and Sociobiology, 61(3). ISBN 0340-5443 print 1432-0762 web, pp. 347–356. January 2007. No electronic version available. External information

2006

• Tim Kovacs, Xavier LLora, Keiki Takadama, The 9th International Workshop on Learning Classifier Systems (IWLCS-2006 Workshop Summary). SIGEVolution, 1(3). ISSN 1931-8499, pp. 31–33. September 2006. PDF, 2429 Kbytes. External information
• James Marshall, Tim Kovacs, A Representational Ecology for Learning Classifier Systems. Proceedings of the 2006 Genetic and Evolutionary Computation Conference (GECCO 2006). ISBN 1-59593-186-4, pp. 1529–1536. July 2006. PDF, 901 Kbytes.
• Tim Kovacs, Manfred Kerber, A study of structural and parametric learning in XCS. Evolutionary Computation, 14(1), pp. 1–19. June 2006. PDF, 359 Kbytes.
• Robert Planque, James Marshall, Tim Kovacs, Francois-Xavier Dechaume-Moncharmont, Nigel R. Franks, Ana Sendova-Franks, It takes two to tango: the role of late recruitment in collective decision making. Proceedings of AISB'06: Adaptation in Artificial and Biological Systems. ISSN 1902956975, pp. 207–207. April 2006. PDF, 34 Kbytes. External information
• James Marshall, Rafal Bogacz, Anna Dornhaus, Nigel R. Franks, Tim Kovacs, Robert Planque, Similar Models of Optimal Decision Making in Social Insect Colonies and in the Primate Brain. Proceedings of AISB'06: Adaptation in Artificial and Biological Systems. ISSN 1902956975, pp. 205–205. April 2006. PDF, 17 Kbytes. External information
• James Marshall, Anna Dornhaus, Nigel Franks, Tim Kovacs, Noise, cost and speed-accuracy trade-offs: decision making in a decentralized system. Journal of the Royal Society: Interface, 3(7). ISBN 1742-5689 (paper) 1742-5662, pp. 243–254. April 2006. PDF, 2076 Kbytes. External information
• James Marshall, Tim Kovacs, Alternative Representations for Artificial Immune Systems. Proceedings of AISB'06: Adaptation in Artificial and Biological Systems. ISSN 1902956975, pp. 9–10. March 2006. PDF, 110 Kbytes.
• Proceedings of AISB'06: Adaptation in Artificial and Biological Systems. Tim Kovacs, James Marshall, (eds.). The Society for the Study of Artificial Intelligence and the Simulation of Behaviour. ISSN 1902956975. March 2006. No electronic version available. External information

2005

• Larry Bull, Tim Kovacs, Foundations of Learning Classifier Systems: An Introduction. Chapter in Foundations of Learning Classifier Systems. ISBN 3-540-25073-5, pp. 1–17. June 2005. No electronic version available.
• Foundations of Learning Classifier Systems. Larry Bull, Tim Kovacs, (eds.). Springer. ISBN 3-540-25073-5. June 2005. No electronic version available. External information
• Steve Cayzer, Jim Smith, James Marshall, Tim Kovacs, What have gene libraries done for AIS?. ICARIS 2005: Proceedings of the Fourth International Conference on Artificial Immune Systems, pp. 86–99. June 2005. PDF, 198 Kbytes.
• Peter Spellward, Tim Kovacs, On the contribution of gene libraries to artificial immune systems. Proceedings of the Genetic and Evolutionary Computation Conference. ISBN 1-59593-010-8, pp. 313–319. June 2005. No electronic version available.

2004

• Zengchang Qin, Tim Kovacs, Evolution of realistic hybrid auctions. Proceedings of the 2004 UK Workshop on Computational Intelligence (UKCI-04), pp. 43–50. September 2004. No electronic version available.
• Tim Kovacs, Manfred Kerber, High classification accuracy does not imply effective genetic search. Proceedings of the 2004 Genetic and Evolutionary Computation Conference (GECCO), LNCS Vol. 3102, pp. 785–796. July 2004. PDF, 314 Kbytes.
• Tim Kovacs, Bibliography of Real-World Classifier Systems Applications. Chapter in Applications of Learning Classifier Systems. ISBN 3-540-21109-8, pp. 300–305. April 2004. PDF, 118 Kbytes.
• Tim Kovacs, Rule Fitness and Pathology in Learning Classifier Systems. Evolutionary Computation , 12(1). ISSN 1063-6560, pp. 99–135. March 2004. PDF, 236 Kbytes.
• Martin Butz, Tim Kovacs, Pier Luca Lanzi, Stewart W. Wilson, Toward a Theory of Generalization and Learning in XCS. IEEE Transactions on Evolutionary Computation, 8(1). ISSN 1089-778X, pp. 28–46. February 2004. PDF, 932 Kbytes.
• Tim Kovacs, Strength or Accuracy: Credit Assignment in Learning Classifier Systems. Springer-Verlag. ISBN 1-85233-770-2. January 2004. No electronic version available. External information

2003

• Alexandre Temporel, Tim Kovacs, A heuristic hill climbing algorithm for mastermind. Proceedings of the 2003 UK Workshop on Computational Intelligence (UKCI-03). ISSN 0862925371, pp. 189–196. September 2003. PDF, 109 Kbytes.
• James A. R. Marshall, Tim Kovacs, Anna R. Dornhaus, Nigel R. Franks, Simulating the evolution of ant behaviour in evaluating nest sites. Advances in Artificial Life - Proceedings of the 7th European Conference on Artificial Life (ECAL), pp. 643–650. August 2003. PDF, 120 Kbytes.
• Tim Kovacs, Pier Luca Lanzi, The 2003 Learning Classifier Systems Bibliography. Chapter in Learning Classifier Systems. ISBN 3-540-20544-6, pp. 187–230. January 2003. No electronic version available.
• Tim Kovacs, XCS's Strength-Based Twin. Part II. Chapter in Learning Classifier Systems. ISBN 3-540-20544-6, pp. 81–98. January 2003. PDF, 374 Kbytes.
• Tim Kovacs, XCS's Strength-Based Twin. Part I. Chapter in Learning Classifier Systems. ISBN 3-540-20544-6, pp. 61–80. January 2003. PDF, 474 Kbytes.
• Tim Kovacs, Stuart I. Reynolds, A Proposal for Population-Based Reinforcement Learning. CSTR-03-001, Department of Computer Science, University of Bristol. January 2003. PDF, 184 Kbytes.

2002

• Tim Kovacs, What should a classifier system learn and how should we measure it?. Journal of Soft Computing, 6 (3-4). ISSN 1432-7643, pp. 171–182. June 2002. No electronic version available.
• Tim Kovacs, Learning Classifier Systems Resources. Journal of Soft Computing, 6 (3-4). ISSN 1432-7643, pp. 240–243. June 2002. PDF, 133 Kbytes.
• Tim Kovacs, Performance and Population State Metrics for Rule-based Learning Systems. Proceedings of the 2002 Congress on Evolutionary Computation (CEC). David Fogel, (eds.), pp. 1781–1786. May 2002. PDF, 312 Kbytes.
• Tim Kovacs, Two Views of Classifier Systems. Chapter in Advances in Learning Classifier Systems. P. L. Lanzi, W. Stolzmann, S. W. Wilson, (eds.). ISBN 3-540-43793-2, pp. 74–87. April 2002. PDF, 203 Kbytes.
• Tim Kovacs, Strength or Accuracy: Credit Assignment in Learning Classifier Systems. PhD thesis. School of Computer Science. University of Birmingham. February 2002. No electronic version available. External information

2001

• Tim Kovacs, Towards a Theory of Strong Overgeneral Classifiers. Chapter in Foundations of Genetic Algorithms 6. Worthy Martin, William Spears, (eds.), pp. 165–184. August 2001. PDF, 110 Kbytes.
• Martin V. Butz, Tim Kovacs, Pier Luca Lanzi, Stewart W. Wilson, How XCS Evolves Accurate Classifiers. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001). Lee Spector et al. , (eds.), pp. 927–934. July 2001. PDF, 284 Kbytes.
• Tim Kovacs, What should a classifier system learn?. Proceedings of the 2001 Congress on Evolutionary Computation (CEC). Jong-Hwan Kim, (eds.), pp. 775–782. May 2001. PDF, 113 Kbytes.
• Tim Kovacs, Pier Luca Lanzi, A Bigger Learning Classifier Systems Bibliography. Chapter in Advances in Learning Classifier Systems. P. L. Lanzi, W. Stolzmann, S. W. Wilson, (eds.), pp. 213–249. April 2001. No electronic version available. External information
• Tim Kovacs, Manfred Kerber, What Makes a Problem Hard for XCS?. Chapter in Advances in Learning Classifier Systems. P. L. Lanzi, W. Stolzmann, S. W. Wilson, (eds.), pp. 80–99. April 2001. PDF, 264 Kbytes.

2000

• Tim Kovacs, Manfred Kerber, What makes a problem hard for XCS?. Proceedings of the Third International Workshop on Learning Classifier Systems (IWLCS-2000), in the Joint Workshops of SAB 2000 and PPSN 2000. Pier Luca Lanzi, Wolfgang Stolzmann, Stewart W. Wilson, (eds.). July 2000. No electronic version available. External information
• Tim Kovacs, Manfred Kerber, Some dimensions of problem complexity for XCS. Proceedings of the GECCO-2000 Graduate Student Workshop. Annie S. Wu, (eds.). July 2000. No electronic version available. External information
• Tim Kovacs, Pier Luca Lanzi, A Learning Classifier Systems Bibliography. Chapter in Learning Classifier Systems. From Foundations to Applications. P. L. Lanzi, W. Stolzmann, S. W. Wilson, (eds.), pp. 321–347. March 2000. No electronic version available. External information
• Tim Kovacs, Strength or Accuracy? Fitness Calculation in Learning Classifier Systems. Chapter in Learning Classifier Systems. From Foundations to Applications. P. L. Lanzi, W. Stolzmann, S. W. Wilson, (eds.), pp. 143–160. March 2000. PDF, 203 Kbytes.

1999

• Tim Kovacs, Deletion Schemes for Classifier Systems. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 99). W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, R. E. Smith, (eds.), pp. 329–336. July 1999. PDF, 388 Kbytes.

1997

• Tim Kovacs, XCS Classifier System Reliably Evolves Accurate, Complete, and Minimal Representations for Boolean Functions.. Chapter in Soft Computing in Engineering Design and Manufacturing. Roy, Chawdhry, Pant, (eds.), pp. 59–68. August 1997. PDF, 269 Kbytes.