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2010 – 2019
- 2018
[c41]Kazuma Matsumoto, Ryo Takano, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
XCSR based on compressed input by deep neural network for high dimensional data. GECCO (Companion) 2018: 1418-1425- [c40]Takato Tatsumi, Tim Kovacs, Keiki Takadama:
XCS-CR: determining accuracy of classifier by its collective reward in action set toward environment with action noise. GECCO (Companion) 2018: 1457-1464 - [c39]Fumito Uwano, Koji Dobashi, Keiki Takadama, Tim Kovacs:
Generalizing rules by random forest-based learning classifier systems for high-dimensional data mining. GECCO (Companion) 2018: 1465-1472 - [c38]Caili Zhang, Takato Tatsumi, Hiyoyuki Sato, Tim Kovacs, Keiki Takadama:
Classifier generalization for comprehensive classifiers subsumption in XCS. GECCO (Companion) 2018: 1854-1861 - 2017
- [j12]Kazuma Matsumoto, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
XCSR Learning from Compressed Data Acquired by Deep Neural Network. J. Adv. Comput. Intell. Intell. Informatics 21(5): 856-867 (2017) - [c37]Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
Applying variance-based Learning Classifier System without Convergence of Reward Estimation into various Reward distribution. CEC 2017: 2630-2637 - 2016
- [j11]Fumito Uwano, Naoki Tatebe, Masaya Nakata, Keiki Takadama, Tim Kovacs:
Reinforcement Learning with Internal Reward for Multi-Agent Cooperation: A Theoretical Approach. EAI Endorsed Trans. Collab. Comput. 2(8): e2 (2016) - [j10]Akinori Murata, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
Optimization of Aircraft Landing Route and Order: An approach of Hierarchical Evolutionary Computation. EAI Endorsed Trans. Self Adapt. Syst. 2(6): e5 (2016) - [c36]Kazuma Matsumoto, Yusuke Tajima, Rei Saito, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
Learning classifier system with deep autoencoder. CEC 2016: 4739-4746 - [c35]Tim Kovacs, Simon Rawles, Larry Bull, Masaya Nakata, Keiki Takadama:
XCS-DH: Minimal default hierarchies in XCS. CEC 2016: 4747-4754 - [c34]Takato Tatsumi, Takahiro Komine, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
Variance-based Learning Classifier System without Convergence of Reward Estimation. GECCO (Companion) 2016: 67-68 - [c33]Rei Saito, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
Preventing Incorrect Opinion Sharing with Weighted Relationship Among Agents. HCI (5) 2016: 50-62 - [c32]Caili Zhang, Takato Tatsumi, Masaya Nakata, Keiki Takadama, Hiroyuki Sato, Tim Kovacs:
Extracting Different Abstracted Level Rule with Variance-Based LCS. SCIS&ISIS 2016: 160-165 - 2015
- [j9]Tim Kovacs, Muhammad Iqbal, Kamran Shafi, Ryan J. Urbanowicz
:
Special issue on the 20th anniversary of XCS. Evol. Intell. 8(2-3): 51-53 (2015) - [j8]Masaya Nakata, Tim Kovacs, Keiki Takadama:
XCS-SL: a rule-based genetic learning system for sequence labeling. Evol. Intell. 8(2-3): 133-148 (2015) - [c31]Fumito Uwano, Naoki Tatebe, Masaya Nakata, Keiki Takadama, Tim Kovacs:
Reinforcement Learning with Internal Reward for Multi-Agent Cooperation: A Theoretical Approach. BICT 2015: 332-339 - [c30]Akinori Murata, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
Optimization of Aircraft Landing Route and Order: An approach of Hierarchical Evolutionary Computation. BICT 2015: 340-347 - [c29]Masaya Nakata, Pier Luca Lanzi, Tim Kovacs, Will Neil Browne, Keiki Takadama:
How should Learning Classifier Systems cover a state-action space? CEC 2015: 3012-3019 - [c28]Tom Pickering, Tim Kovacs:
TP-XCS: An XCS classifier system with fixed-length memory for reinforcement learning. CEC 2015: 3020-3025 - 2014
- [c27]Masaya Nakata, Pier Luca Lanzi, Tim Kovacs, Keiki Takadama:
Complete action map or best action map in accuracy-based reinforcement learning classifier systems. GECCO 2014: 557-564 - [c26]Masaya Nakata, Tim Kovacs, Keiki Takadama:
A modified XCS classifier system for sequence labeling. GECCO 2014: 565-572 - [c25]Masaya Nakata, Tim Kovacs, Keiki Takadama:
Messy Coding in the XCS Classifier System for Sequence Labeling. PPSN 2014: 191-200 - 2013
- [c24]Tim Kovacs, Robin Tindale:
Analysis of the niche genetic algorithm in learning classifier systems. GECCO 2013: 1069-1076 - 2012
- [p1]Tim Kovacs:
Genetics-Based Machine Learning. Handbook of Natural Computing 2012: 937-986 - [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. Mach. Learn. 84(1-2): 7-49 (2011) - [c23]Tim Kovacs, Narayanan Unny Edakunni, Gavin Brown:
Accuracy exponentiation in UCS and its effect on voting margins. GECCO 2011: 1251-1258 - [c22]Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs:
Online, GA based mixture of experts: a probabilistic model of ucs. GECCO 2011: 1267-1274 - [c21]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. Nat. Comput. 8(1): 3-27 (2009) - [c20]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:
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 [contents] - 2007
- [c19]Gavin Brown, Tim Kovacs, James A. R. Marshall:
UCSpv: principled voting in UCS rule populations. GECCO 2007: 1774-1781 - [c18]Tim Kovacs, Larry Bull:
Toward a better understanding of rule initialisation and deletion. GECCO (Companion) 2007: 2777-2780 - [c17]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:
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 [contents] - 2006
- [j5]Tim Kovacs, Manfred Kerber:
A Study of Structural and Parametric Learning in XCS. Evol. Comput. 14(1): 1-19 (2006) - [c16]James A. R. Marshall, Tim Kovacs:
A representational ecology for learning classifier systems. GECCO 2006: 1529-1536 - 2005
- [c15]Peter Spellward, Tim Kovacs:
On the contribution of gene libraries to artificial immune systems. GECCO 2005: 313-319 - [c14]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. Evol. Comput. 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. Evol. Comput. 8(1): 28-46 (2004) - [c13]Tim Kovacs, Manfred Kerber:
High Classification Accuracy Does Not Imply Effective Genetic Search. GECCO (2) 2004: 785-796 - 2003
- [c12]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]Tim Kovacs:
Learning classifier systems resources. Soft Comput. 6(3-4): 240-243 (2002) - [c11]Tim Kovacs:
Performance and population state metrics for rule-based learning systems. IEEE Congress on Evolutionary Computation 2002: 1781-1786 - [c10]Tim Kovacs:
XCS's Strength-Based Twin: Part I. IWLCS 2002: 61-80 - [c9]Tim Kovacs:
XCS's Strength-Based Twin: Part II. IWLCS 2002: 81-98 - [c8]Tim Kovacs:
The 2003 Learning Classifier Systems Bibliography. IWLCS 2002: 187-230 - 2001
- [c7]Tim Kovacs:
What should a classifier system learn? CEC 2001: 775-782 - [c6]Tim Kovacs:
Two Views of Classifier Systems. IWLCS 2001: 74-87 - 2000
- [c5]Tim Kovacs:
Towards a Theory of Strong Overgeneral Classifiers. FOGA 2000: 165-184 - [c4]Tim Kovacs, Manfred Kerber:
What Makes a Problem Hard for XCS? IWLCS 2000: 80-102 - [c3]Tim Kovacs, Pier Luca Lanzi:
A Bigger Learning Classifier Systems Bibliography. IWLCS 2000: 213-252
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 2024-10-07 21:17 CEST by the dblp team
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