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Martin V. Butz: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Martin V. Butz
    Kernel-based, ellipsoidal conditions in the real-valued XCS classifier system. [Citation Graph (0, 0)][DBLP]
    GECCO, 2005, pp:1835-1842 [Conf]
  2. Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
    Bounding Learning Time in XCS. [Citation Graph (0, 0)][DBLP]
    GECCO (2), 2004, pp:739-750 [Conf]
  3. Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
    Gradient-Based Learning Updates Improve XCS Performance in Multistep Problems. [Citation Graph (0, 0)][DBLP]
    GECCO (2), 2004, pp:751-762 [Conf]
  4. Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
    Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure. [Citation Graph (0, 0)][DBLP]
    GECCO, 2006, pp:1457-1464 [Conf]
  5. Martin V. Butz, Martin Pelikan
    Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions. [Citation Graph (0, 0)][DBLP]
    GECCO, 2006, pp:1449-1456 [Conf]
  6. Martin V. Butz, Martin Pelikan, Xavier Llorà, David E. Goldberg
    Extracted global structure makes local building block processing effective in XCS. [Citation Graph (0, 0)][DBLP]
    GECCO, 2005, pp:655-662 [Conf]
  7. Martin Pelikan, Kumara Sastry, Martin V. Butz, David E. Goldberg
    Hierarchical BOA on random decomposable problems. [Citation Graph (0, 0)][DBLP]
    GECCO, 2006, pp:431-432 [Conf]
  8. Arnaud Quirin, Jerzy J. Korczak, Martin V. Butz, David E. Goldberg
    Analysis and Evaluation of Learning Classifier Systems applied to Hyperspectral Image Classification. [Citation Graph (0, 0)][DBLP]
    ISDA, 2005, pp:280-285 [Conf]
  9. Jaume Bacardit, David E. Goldberg, Martin V. Butz, Xavier Llorà, Josep Maria Garrell i Guiu
    Speeding-Up Pittsburgh Learning Classifier Systems: Modeling Time and Accuracy. [Citation Graph (0, 0)][DBLP]
    PPSN, 2004, pp:1021-1031 [Conf]
  10. Martin V. Butz, Pier Luca Lanzi, Xavier Llorà, David E. Goldberg
    Knowledge Extraction and Problem Structure Identification in XCS. [Citation Graph (0, 0)][DBLP]
    PPSN, 2004, pp:1051-1060 [Conf]
  11. Cláudio F. Lima, Martin Pelikan, Kumara Sastry, Martin V. Butz, David E. Goldberg, Fernando G. Lobo
    Substructural Neighborhoods for Local Search in the Bayesian Optimization Algorithm. [Citation Graph (0, 0)][DBLP]
    PPSN, 2006, pp:232-241 [Conf]
  12. Martin Pelikan, Kumara Sastry, Martin V. Butz, David E. Goldberg
    Performance of Evolutionary Algorithms on Random Decomposable Problems. [Citation Graph (0, 0)][DBLP]
    PPSN, 2006, pp:788-797 [Conf]
  13. Martin V. Butz, Martin Pelikan, Xavier Llorà, David E. Goldberg
    Automated Global Structure Extraction for Effective Local Building Block Processing in XCS. [Citation Graph (0, 0)][DBLP]
    Evolutionary Computation, 2006, v:14, n:3, pp:345-380 [Journal]
  14. Martin V. Butz, Kumara Sastry, David E. Goldberg
    Strong, Stable, and Reliable Fitness Pressure in XCS due to Tournament Selection. [Citation Graph (0, 0)][DBLP]
    Genetic Programming and Evolvable Machines, 2005, v:6, n:1, pp:53-77 [Journal]
  15. Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
    Gradient descent methods in learning classifier systems: improving XCS performance in multistep problems. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2005, v:9, n:5, pp:452-473 [Journal]
  16. Martin V. Butz, Tim Kovacs, Pier Luca Lanzi, Stewart W. Wilson
    Toward a theory of generalization and learning in XCS. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2004, v:8, n:1, pp:28-46 [Journal]
  17. Martin V. Butz
    Learning classifier systems. [Citation Graph (0, 0)][DBLP]
    GECCO (Companion), 2007, pp:3035-3056 [Conf]
  18. Pier Luca Lanzi, Martin V. Butz, David E. Goldberg
    Empirical analysis of generalization and learning in XCS with gradient descent. [Citation Graph (0, 0)][DBLP]
    GECCO, 2007, pp:1814-1821 [Conf]
  19. Jaume Bacardit, Martin V. Butz
    Data Mining in Learning Classifier Systems: Comparing XCS with GAssist. [Citation Graph (0, 0)][DBLP]
    IWLCS, 2005, pp:282-290 [Conf]
  20. Jaume Bacardit, David E. Goldberg, Martin V. Butz
    Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule. [Citation Graph (0, 0)][DBLP]
    IWLCS, 2005, pp:291-307 [Conf]
  21. Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
    Effect of Pure Error-Based Fitness in XCS. [Citation Graph (0, 0)][DBLP]
    IWLCS, 2005, pp:104-114 [Conf]
  22. Giovanni Pezzulo, Gianluca Baldassarre, Martin V. Butz, Cristiano Castelfranchi, Joachim Hoffmann
    From Actions to Goals and Vice-Versa: Theoretical Analysis and Models of the Ideomotor Principle and TOTE. [Citation Graph (0, 0)][DBLP]
    SAB ABiALS, 2006, pp:73-93 [Conf]
  23. Martin V. Butz, Olivier Sigaud, Giovanni Pezzulo, Gianluca Baldassarre
    Anticipations, Brains, Individual and Social Behavior: An Introduction to Anticipatory Systems. [Citation Graph (0, 0)][DBLP]
    SAB ABiALS, 2006, pp:1-18 [Conf]
  24. Martin V. Butz, David E. Goldberg, Pier Luca Lanzi, Kumara Sastry
    Problem solution sustenance in XCS: Markov chain analysis of niche support distributions and the impact on computational complexity. [Citation Graph (0, 0)][DBLP]
    Genetic Programming and Evolvable Machines, 2007, v:8, n:1, pp:5-37 [Journal]

  25. Context-dependent predictions and cognitive arm control with XCSF. [Citation Graph (, )][DBLP]


  26. An analysis of matching in learning classifier systems. [Citation Graph (, )][DBLP]


  27. Self-adaptive mutation in XCSF. [Citation Graph (, )][DBLP]


  28. Towards increasing learning speed and robustness of XCSF: experimenting with larger offspring set sizes. [Citation Graph (, )][DBLP]


  29. Learning classifier systems. [Citation Graph (, )][DBLP]


  30. Performance of evolutionary algorithms on NK landscapes with nearest neighbor interactions and tunable overlap. [Citation Graph (, )][DBLP]


  31. On the scalability of XCS(F). [Citation Graph (, )][DBLP]


  32. Learning sensorimotor control structures with XCSF: redundancy exploitation and dynamic control. [Citation Graph (, )][DBLP]


  33. NEAT in increasingly non-linear control situations. [Citation Graph (, )][DBLP]


  34. Evolving robust controller parameters using covariance matrix adaptation. [Citation Graph (, )][DBLP]


  35. Learning classifier systems. [Citation Graph (, )][DBLP]


  36. A comparative study: function approximation with LWPR and XCSF. [Citation Graph (, )][DBLP]


  37. Combining Gradient-Based With Evolutionary Online Learning: An Introduction to Learning Classifier Systems. [Citation Graph (, )][DBLP]


  38. Encoding Complete Body Models Enables Task Dependent Optimal Behavior. [Citation Graph (, )][DBLP]


  39. Emergent Effector-Independent Internal Spaces: Adaptation and Intermanual Learning Transfer in Humans and Neural Networks. [Citation Graph (, )][DBLP]


  40. Learning Classifier Systems: Looking Back and Glimpsing Ahead. [Citation Graph (, )][DBLP]


  41. The Scared Robot: Motivations in a Simulated Robot Arm. [Citation Graph (, )][DBLP]


  42. Controlling a Four Degree of Freedom Arm in 3D Using the XCSF Learning Classifier System. [Citation Graph (, )][DBLP]


  43. Agent Learning Instead of Behavior Implementation for Simulations - A Case Study Using Classifier Systems. [Citation Graph (, )][DBLP]


  44. Anticipatory Learning Classifier Systems and Factored Reinforcement Learning. [Citation Graph (, )][DBLP]


  45. From Sensorimotor to Higher-Level Cognitive Processes: An Introduction to Anticipatory Behavior Systems. [Citation Graph (, )][DBLP]


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