Tim Kovacs

According to our database, Tim Kovacs authored at least 53 papers between 1999 and 2018.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2018

Classifier generalization for comprehensive classifiers subsumption in XCS.

Caili Zhang, Takato Tatsumi, Hiyoyuki Sato, Tim Kovacs, Keiki Takadama

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

Generalizing rules by random forest-based learning classifier systems for high-dimensional data mining.

Fumito Uwano, Koji Dobashi, Keiki Takadama, Tim Kovacs

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

XCS-CR: determining accuracy of classifier by its collective reward in action set toward environment with action noise.

Takato Tatsumi, Tim Kovacs, Keiki Takadama

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

XCSR based on compressed input by deep neural network for high dimensional data.

Kazuma Matsumoto, Ryo Takano, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

2017

XCSR Learning from Compressed Data Acquired by Deep Neural Network.

Kazuma Matsumoto, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama

J. Adv. Comput. Intell. Intell. Informatics, 2017

Applying variance-based Learning Classifier System without Convergence of Reward Estimation into various Reward distribution.

Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama

Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016

Optimization of Aircraft Landing Route and Order: An approach of Hierarchical Evolutionary Computation.

Akinori Murata, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama

EAI Endorsed Trans. Self Adapt. Syst., 2016

Reinforcement Learning with Internal Reward for Multi-Agent Cooperation: A Theoretical Approach.

Fumito Uwano, Naoki Tatebe, Masaya Nakata, Keiki Takadama, Tim Kovacs

EAI Endorsed Trans. Collab. Comput., 2016

Extracting Different Abstracted Level Rule with Variance-Based LCS.

Caili Zhang, Takato Tatsumi, Masaya Nakata, Keiki Takadama, Hiroyuki Sato, Tim Kovacs

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

Preventing Incorrect Opinion Sharing with Weighted Relationship Among Agents.

Rei Saito, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama

Proceedings of the Human Interface and the Management of Information: Applications and Services, 2016

Variance-based Learning Classifier System without Convergence of Reward Estimation.

Takato Tatsumi, Takahiro Komine, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama

Proceedings of the Genetic and Evolutionary Computation Conference, 2016

Learning classifier system with deep autoencoder.

Kazuma Matsumoto, Yusuke Tajima, Rei Saito, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama

Proceedings of the IEEE Congress on Evolutionary Computation, 2016

XCS-DH: Minimal default hierarchies in XCS.

Tim Kovacs, Simon Rawles, Larry Bull, Masaya Nakata, Keiki Takadama

Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2015

XCS-SL: a rule-based genetic learning system for sequence labeling.

Masaya Nakata, Tim Kovacs, Keiki Takadama

Evol. Intell., 2015

Special issue on the 20th anniversary of XCS.

Tim Kovacs, Muhammad Iqbal, Kamran Shafi, Ryan J. Urbanowicz

Evol. Intell., 2015

TP-XCS: An XCS classifier system with fixed-length memory for reinforcement learning.

Tom Pickering, Tim Kovacs

Proceedings of the IEEE Congress on Evolutionary Computation, 2015

How should Learning Classifier Systems cover a state-action space?

Masaya Nakata, Pier Luca Lanzi, Tim Kovacs, Will Neil Browne, Keiki Takadama

Proceedings of the IEEE Congress on Evolutionary Computation, 2015

2014

Messy Coding in the XCS Classifier System for Sequence Labeling.

Masaya Nakata, Tim Kovacs, Keiki Takadama

Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014

Complete action map or best action map in accuracy-based reinforcement learning classifier systems.

Masaya Nakata, Pier Luca Lanzi, Tim Kovacs, Keiki Takadama

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

A modified XCS classifier system for sequence labeling.

Masaya Nakata, Tim Kovacs, Keiki Takadama

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

2013

Analysis of the niche genetic algorithm in learning classifier systems.

Tim Kovacs, Robin Tindale

Proceedings of the Genetic and Evolutionary Computation Conference, 2013

2012

Genetics-Based Machine Learning.

Tim Kovacs

Proceedings of the Handbook of Natural Computing, 2012

2011

On the analysis and design of software for reinforcement learning, with a survey of existing systems.

Tim Kovacs, Robert Egginton

Mach. Learn., 2011

Boosting as a Product of Experts.

Narayanan Unny Edakunni, Gary Brown, Tim Kovacs

Proceedings of the UAI 2011, 2011

Accuracy exponentiation in UCS and its effect on voting margins.

Tim Kovacs, Narayanan Unny Edakunni, Gavin Brown

Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Online, GA based mixture of experts: a probabilistic model of ucs.

Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs

Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

2009

Intrusion detection with evolutionary learning classifier systems.

Kamran Shafi, Tim Kovacs, Hussein A. Abbass, Weiping Zhu

Nat. Comput., 2009

Modeling UCS as a mixture of experts.

Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, James A. R. Marshall

Proceedings of the Genetic and Evolutionary Computation Conference, 2009

2007

Bayesian estimation of rule accuracy in UCS.

James A. R. Marshall, Gavin Brown, Tim Kovacs

Proceedings of the Genetic and Evolutionary Computation Conference, 2007

Toward a better understanding of rule initialisation and deletion.

Tim Kovacs, Larry Bull

Proceedings of the Genetic and Evolutionary Computation Conference, 2007

UCSpv: principled voting in UCS rule populations.

Gavin Brown, Tim Kovacs, James A. R. Marshall

Proceedings of the Genetic and Evolutionary Computation Conference, 2007

2006

A Study of Structural and Parametric Learning in XCS.

Tim Kovacs, Manfred Kerber

Evol. Comput., 2006

A representational ecology for learning classifier systems.

James A. R. Marshall, Tim Kovacs

Proceedings of the Genetic and Evolutionary Computation Conference, 2006

2005

What Have Gene Libraries Done for AIS?

Steve Cayzer, Jim Smith, James A. R. Marshall, Tim Kovacs

Proceedings of the Artificial Immune Systems: 4th International Conference, 2005

On the contribution of gene libraries to artificial immune systems.

Peter Spellward, Tim Kovacs

Proceedings of the Genetic and Evolutionary Computation Conference, 2005

2004

Strength or accuracy: credit assignment in learning classifier systems.

Tim Kovacs

PhD thesis, 2004

Toward a theory of generalization and learning in XCS.

Martin V. Butz, Tim Kovacs, Pier Luca Lanzi, Stewart W. Wilson

IEEE Trans. Evol. Comput., 2004

Rule Fitness and Pathology in Learning Classifier Systems.

Tim Kovacs

Evol. Comput., 2004

High Classification Accuracy Does Not Imply Effective Genetic Search.

Tim Kovacs, Manfred Kerber

Proceedings of the Genetic and Evolutionary Computation, 2004

2003

Simulating the Evolution of Ant Behaviour in Evaluating Nest Sites.

James A. R. Marshall, Tim Kovacs, Anna R. Dornhaus, Nigel R. Franks

Proceedings of the Advances in Artificial Life, 7th European Conference, 2003

2002

Learning classifier systems resources.

Tim Kovacs

Soft Comput., 2002

What should a classifier system learn and how should we measure it?

Tim Kovacs

Soft Comput., 2002

The 2003 Learning Classifier Systems Bibliography.

Tim Kovacs

Proceedings of the Learning Classifier Systems, 5th International Workshop, 2002

XCS's Strength-Based Twin: Part II.

Tim Kovacs

Proceedings of the Learning Classifier Systems, 5th International Workshop, 2002

XCS's Strength-Based Twin: Part I.

Tim Kovacs

Proceedings of the Learning Classifier Systems, 5th International Workshop, 2002

Performance and population state metrics for rule-based learning systems.

Tim Kovacs

Proceedings of the 2002 Congress on Evolutionary Computation, 2002

2001

Two Views of Classifier Systems.

Tim Kovacs

Proceedings of the Advances in Learning Classifier Systems, 4th International Workshop, 2001

What should a classifier system learn?

Tim Kovacs

Proceedings of the 2001 Congress on Evolutionary Computation, 2001

2000

A Bigger Learning Classifier Systems Bibliography.

Tim Kovacs, Pier Luca Lanzi

Proceedings of the Advances in Learning Classifier Systems, Third International Workshop, 2000

What Makes a Problem Hard for XCS?

Tim Kovacs, Manfred Kerber

Proceedings of the Advances in Learning Classifier Systems, Third International Workshop, 2000

Towards a Theory of Strong Overgeneral Classifiers.

Tim Kovacs

Proceedings of the Sixth Workshop on Foundations of Genetic Algorithms, 2000

1999

A Learning Classifier Systems Bibliography.

Tim Kovacs, Pier Luca Lanzi

Proceedings of the Learning Classifier Systems, From Foundations to Applications, 1999

Strength or Accuracy? Fitness Calculation in Learning Classifier Systems.

Tim Kovacs

Proceedings of the Learning Classifier Systems, From Foundations to Applications, 1999