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Tim Kovacs
2010 – today
- 2012
[i1]Narayanan Unny Edakunni, Gary Brown, Tim Kovacs: Boosting as a Product of Experts. CoRR abs/1202.3716 (2012)- 2011
- [j7]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): 7-49 (2011)
- [c21]Tim Kovacs, Narayanan Unny Edakunni, Gavin Brown: Accuracy exponentiation in UCS and its effect on voting margins. GECCO 2011: 1251-1258
- [c20]Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs: Online, GA based mixture of experts: a probabilistic model of ucs. GECCO 2011: 1267-1274
- [c19]Narayanan Unny Edakunni, Gary Brown, Tim Kovacs: Boosting as a Product of Experts. UAI 2011: 187-194
2000 – 2009
- 2009
- [j6]Kamran Shafi, Tim Kovacs, Hussein A. Abbass, Weiping Zhu: Intrusion detection with evolutionary learning classifier systems. Natural Computing 8(1): 3-27 (2009)
- [c18]Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, James A. R. Marshall: Modeling UCS as a mixture of experts. GECCO 2009: 1187-1194
- 2008
- [e2]Jaume Bacardit, Ester Bernadó-Mansilla, Martin V. Butz, Tim Kovacs, Xavier Llorà, Keiki Takadama (Eds.): Learning Classifier Systems, 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers. Lecture Notes in Computer Science 4998, Springer 2008, ISBN 978-3-540-88137-7
- 2007
- [c17]Gavin Brown, Tim Kovacs, James A. R. Marshall: UCSpv: principled voting in UCS rule populations. GECCO 2007: 1774-1781
- [c16]Tim Kovacs, Larry Bull: Toward a better understanding of rule initialisation and deletion. GECCO (Companion) 2007: 2777-2780
- [c15]James A. R. Marshall, Gavin Brown, Tim Kovacs: Bayesian estimation of rule accuracy in UCS. GECCO (Companion) 2007: 2831-2834
- [e1]Tim Kovacs, Xavier Llorà, Keiki Takadama, Pier Luca Lanzi, Wolfgang Stolzmann, Stewart W. Wilson (Eds.): Learning Classifier Systems, International Workshops, IWLCS 2003-2005, Revised Selected Papers. Lecture Notes in Computer Science 4399, Springer 2007, ISBN 978-3-540-71230-5
- 2006
- [j5]Tim Kovacs, Manfred Kerber: A Study of Structural and Parametric Learning in XCS. Evolutionary Computation 14(1): 1-19 (2006)
- [c14]James A. R. Marshall, Tim Kovacs: A representational ecology for learning classifier systems. GECCO 2006: 1529-1536
- 2005
- [c13]Peter Spellward, Tim Kovacs: On the contribution of gene libraries to artificial immune systems. GECCO 2005: 313-319
- [c12]Steve Cayzer, Jim Smith, James A. R. Marshall, Tim Kovacs: What Have Gene Libraries Done for AIS? ICARIS 2005: 86-99
- 2004
- [b1]Tim Kovacs: Strength or accuracy: credit assignment in learning classifier systems. Bristol, Univ. 2004, ISBN 1-85233-770-2, pp. 1-307
- [j4]Tim Kovacs: Rule Fitness and Pathology in Learning Classifier Systems. Evolutionary Computation 12(1): 99-135 (2004)
- [j3]Martin V. Butz, Tim Kovacs, Pier Luca Lanzi, Stewart W. Wilson: Toward a theory of generalization and learning in XCS. IEEE Trans. Evolutionary Computation 8(1): 28-46 (2004)
- [c11]Tim Kovacs, Manfred Kerber: High Classification Accuracy Does Not Imply Effective Genetic Search. GECCO (2) 2004: 785-796
- 2003
- [c10]James A. R. Marshall, Tim Kovacs, Anna R. Dornhaus, Nigel R. Franks: Simulating the Evolution of Ant Behaviour in Evaluating Nest Sites. ECAL 2003: 643-650
- 2002
- [j2]Tim Kovacs: What should a classifier system learn and how should we measure it? Soft Comput. 6(3-4): 171-182 (2002)
- [j1]
- [c9]
- [c8]
- [c7]
- 2001
- [c6]
- 2000
- [c5]
- [c4]
- [c3]
1990 – 1999
- 1999
- [c2]Tim Kovacs: Strength or Accuracy? Fitness Calculation in Learning Classifier Systems. Learning Classifier Systems 1999: 143-160
- [c1]Tim Kovacs, Pier Luca Lanzi: A Learning Classifier Systems Bibliography. Learning Classifier Systems 1999: 321-348
Coauthor Index
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last updated on 2012-12-02 21:05 CET by the dblp team