Chair Publications

(publications are in type, year, author order)

 


Journals

(please send a short request for papers that are not linked)



2017

Lohmann, J., & Butz, M. V. (2017). Lost in space: multisensory conflict yields adaptation in spatial representations across frames of reference. Cognitive Processing, (), 1-18. doi:10.1007/s10339-017-0798-5

Lohmann, J., Rolke, B., & Butz, M. V. (2017). In Touch with Mental Rotation: Interactions between Mental and Tactile Rotations and Motor Responses. Experimental Brain Research. doi:10.1007/s00221-016-4861-8

Schrodt, F., Kneissler, J., Ehrenfeld, S., & Butz, M. V. (2017). Mario Becomes Cognitive. Topics in Cognitive Science, 9(2), 1–31. doi:10.1111/tops.12252

2016

Belardinelli, A., Barabas, M., Himmelbach, M., & Butz, M. V. (2016). Anticipatory eye fixations reveal tool knowledge for tool interaction. Experimental Brain Research, 234, 2415-2431. doi: 10.1007/s00221-016-4646-0

Belardinelli, A., Stepper, M. Y., & Butz, M. V. (2016): It's in the eyes: Planning precise manual actions before execution. Journal of Vision, 16. doi: 10.1167/16.1.18

Butz, M. V. (2016). Towards a unified sub-symbolic computational theory of cognition. Frontiers in Psychology 7. doi: 10.3389/fpsyg.2016.00925 

Jung, E., Takahashi, K., Watanabe, K., de la Rosa, St., Butz, M. V., Bülthoff, H. H., & Meilinger, T. (2016): The influence of human body orientation on distance judgments. Frontiers in Psychology, 7. doi: 10.3389/fpsyg.2016.00217

Otte, S., Butz, M. V., Koryakin, D., Becker, F., Liwicki, M., & Zell, A. (2016): Optimizing recurrent reservoirs with neuro-evolution. Neurocomputing, 128-138. doi: 10.1016/j.neucom.2016.01.088

Schrodt, F., & Butz, M. V. (2016): Just imagine! Learning to emulate and infer actions with a stochastic generative architecture. Frontiers in Rob0tic and AI, 3. doi: 10.3389/frobt.2016.00005

2015

Belardinelli, A., & Butz, M. V. (2015). Anticipatory object interaction: Perceptual and motor aspects. Cognitive Processing, 16, Suppl 1, 14-15.

Belardinelli, A., & Butz, M. V. (2015). Action in the eye of the beholder: Goal-oriented gaze strategies. Cognitive Processing, 16, Suppl 1, 15-16.

Belardinelli, A., & Butz, M. V. (2015). Planning with the eyes: End state comfort effects in gaze behaviour. Cognitive Processing, 16, Suppl 1, 65.

Belardinelli, A., Herbort, O., & Butz, M. V. (2015). Goal-oriented gaze strategies afforded by object interaction. Vision Research, 106, 47-57. doi:10.1016/j.visres.2014.11.003

Herbort, O., & Butz, M. V. (2015). Planning grasps for object manipulation: integrating internal preferences and external constrains. Cognitive Processing, 16, Suppl 1, 249-253. doi: 10.1007/s10339-015-0703-z

Kneissler, J., Drugowitsch, J., Friston, K., & Butz, M. V. (2015): Simultaneous learning and filtering without delusions: A Bayes-optimal derivation of combining predictive inference and adaptive filtering. Frontiers in Computational Neuroscience. doi: 10.3389/fncom.2015.00047

Schrodt, F., Layher, G., Neumann, H., & Butz, M. V. (2015): Embodied learning of a generative neural model for biological motion perception and inference. Frontiers in Computational Neuroscience, 9. doi: 10.3389/fncom.2015.00079

Schroeder, P. A., Lohmann, J., Butz, M. V., & Plewnia, C. (2015): Behavioral bias for food reflected in hand movements: A preliminary study with healthy subjects. Cyberpsychology, Behavior, and Social Networking, 19, 120-126. doi: 10.1089/cyber.2015.0311

2014

Butz, M. V., Kutter, E., & Lorenz, C. (2014). Rubber hand illusion affects joint angle perception, PLoS ONE , 9. doi:10.1371/journal.pone.0092854

Herbort, O., Butz, M. V., & Kunde, W. (2014). The contribution of cognitive, kinematic, and dynamic factors to anticipatory grasp selection. Experimental Brain Research. 232, 1677-1688. doi:10.1007/s00221-014-3849-5

Kneissler, J., Stalph, P. O., Drugowitsch, J., & Butz, M. V. (2014): Filtering sensory information with XCSF: Improving learning robustness and robot arm control performance. Evolutionary Computation. doi: 100.1162/EVCO_a_00108

Layher, G., Schrodt, F., Butz, M. V., & Neumann, H. (2014). Adaptive learning in a compartmental model of visual cortex - how feedback enables stable category learning and refinement. Frontiers in Psychology, 5, 1287. doi: 10.3389/fpsyg.2014.01287

2013

Belardinelli, A.,Carbone, A., & Schneider, W. X. (2013). Classification of multiscale spatiotemporal energy features or video segmentation and dynamic objects prioritisation. Pattern Recognition Letters, 34, Issue 7, May 2013, 713-722. doi: 10.1016/j.patrec.2012.09.005

Butz, M. V. (2013). Separating goals from behavioral control: Implications from learning predictive modularizations. New Ideas in Psychology, 31, 302-312. doi: 10.1016/j.newideapsych.2013.04.001

Ehrenfeld, S., & Butz, M. V. (2013). The modular modality frame model: continuous body state estimation and plausibility-weighted information fusion.  Biological Cybernetics, 107,  61-82. doi: 10.1007/s00422-012-0526-2

Ehrenfeld, S., Herbort, O., & Butz, M. V. (2013). Modular neuron-based body estimation: Maintaining consistency over different limbs, modalities, and frames of reference. Frontiers in Computational Neuroscience, 7, 148. doi: 10.3389/fncom.2013.00148

Lohmann, J., Herbort, O., & Butz, M. V. (2013). Modeling the temporal dynamics of visual working memory. Cognitive Systems Research, 24, 80-86. doi: 10.1016/j.cogsys.2012.12.009

Sigaud, O., Butz, M. V., Pezzulo, G., & Herbort, O. (2013). The anticipatory construction of reality as a central concern for psychology and robotics. New Ideas in Pschology, 31, 217 - 220. doi: 10.1016/j.newideapsych.2012.12.004

2012

Butz, M. V., Belardinelli, A., & Ehrenfeld, S. (2012). Modeling body state-dependent multisensory integration. Cognitive Processing, 13(1), 113-116. doi: 10.1007/s10339-012-0471-y

Butz, M. V., Goldberg, D. E., Llorà, X., & Stalph, P. (2012).  Resource management and scalability of the XCSF learning system. Theoretical Computer Science, 425, 126-141. doi: 10.1016/j.tcs.2010.07.007

Butz, M. V., & Sigaud, O. (2012). XCSF with local deletion: preventing detrimental forgetting. Evolutionary Intelligence, 5, 117-127. Berlin Heidelberg: Springer. doi:10.1007/s12065-012-0077-4

Endler, A., Rey, G. D., & Butz, M. V. (2012). Towards motivation-based adaptation of difficulty in e-learning programs. Australasian Journal of Educational Technology, 28, 1119-1135.

Herbort, O. (2012). Where to grasp a tool? Task-dependent adjustments of tool transformations by tool users. Journal of Psychology, 220(1), 37-43. doi: 10.1027/2151-2604/a000089

Herbort, O., & Butz, M. V. (2012). The continuous end-state comfort effect: Weighted integration of multiple biases. Psychological Research, 76, 345-363. doi: 10.1007/s00426-011-0334-7

Herbort, O., & Butz, M. V. (2012). Too good to be true? Ideomotor theory from a computational perspective. Frontiers in Psychology, 3, 494. doi: 10.3389/fpsyg.2012.00494

Herbort, O., Koning, A., van Uem, J., & Meulenbroek, R. (2012). The end-state comfort effect facilitates joint action. Acta Psychologica, 193(3), 404-416. doi:10.1016/j.actpsy.2012.01.001

Kirsch, W., Herbort, O., Butz, M. V., & Kunde, W. (2012). Influence of motor planning on distance perception within the peripersonal space. PLoS ONE 7(4): e34880, doi:10.1371/journal.pone 0034880 pdf

Koryakin, D., Lohmann, J., & Butz, M. V. (2012). Balanced echo state networks. Neural Networks, 36, 35-45. doi: 10.1016/j.neunet.2012.08.008

Stalph, P., & Butz, M. V. (2012). Learning local linear Jacobians for flexible and adaptive robot arm control. Genetic Programming and Evolvable Machines, 1-21. doi: 10.1007/s10710-011-9147-0

Stalph, P., Rubinsztajn, J., Sigaud, O., & Butz, M. V. (2012). Function approximation with LWPR and XCSF: A comparative study. Evolutionary Intelligence, 5, 103-116. doi: 10.1007/s12065-012-0082-7

2011

Butz, M. V., Linhardt, M. J., & Lönneker, T. D. (2011). Effective racing on partially observable tracks: Indirectly coupling anticipatory egocentric sensors with motor commands. IEEE Transactions on Computational Intelligence and AI in Games, 3, 31-42. doi:10.1109/TCIAIG.2010.2096426

Herbort, O., & Butz, M. V. (2011). Habitual and goal-directed factors in (everyday) object handling.  Experimental Brain Research, 213, 371-382. doi: 10.1007/s00221-011-2787-8

Sugita, Y., Tani, J., & Butz, M. V. (2011). Simultaneously emerging Braitenberg codes and semantic compositionality. Adaptive Behavior, 19, 295-316. doi: 10.1177/1059712311416871

2010

Butz, M. V., Shirinov, E., & Reif, K. (2010). Self-organizing sensorimotor maps plus internal motivations yield animal-like behavior. Adaptive Behavior, 18, 315-337. doi: 10.1177/1059712310376842

Butz, M. V., Thomaschke, R., Linhardt, M. J., & Herbort, O. (2010). Remapping motion across modalities: Tactile rotations influence visual motion judgments. Experimental Brain Research, 207, 1-11. doi: 10.1007/s00221-010-2420-2

Herbort O., & Butz , M. V. (2010). Planning and control of hand orientation in grasping movementsExperimental Brain Research, 202, 867-878. doi: 10.1007/s00221-010-2191-9

Loiacono, D., Lanzi, P. L., Togelius, J., Onieva, E., Pelta, D. A., Butz, M. V., Lönneker, T. D., Cardamone, L., Perez, D., Sáez, Y., Preuss, M., & Quadflieg, J. (2010). The 2009 simulated car racing championship. IEEE Transactions on Computational Intelligence and AI in Games, 2, 131-147. doi: 10.1109/TCIAIG.2010.2050590

2009

Butz, M. V., & Lanzi, P. L. (2009). Sequential problems that test generalization in learning classifier systems. Evolutionary Intelligence, 2, 141-147. doi:10.1007/s12065-009-0019-y

Herbort, O., & Butz, M. V. (2009). Anticipatory planning of sequential hand and finger movements. Journal of Motor Behavior, 41, 561-569. doi: 10.3200/35-09-003-RA

2008

Butz, M. V. (2008). How and why the brain lays the foundations for a conscious self. Constructivist Foundations, 4, 1-42.

Butz, M. V. (2008). Intentions and mirror neurons: From the individual to overall social reality. Commentary. Constructivist Foundations, 3, 87-89.

Butz, M. V. (2008). Sensomotorische Raumrepräsentationen. Informatik-Spektrum, 31, 237-240. doi: 10.1007/s00287-008-0243-3

Butz, M. V., Lanzi, P.  L., & Wilson, S. W. (2008). Function approximation with XCS: Hyperellipsoidal conditions, recursive least squares, and compaction. IEEE Transactions on Evolutionary Computation, 12, 355-376. doi: 10.1109/TEVC.2007.903551

2007

Butz, M. V., Herbort, O., & Hoffmann, J. (2007). Exploiting redundancy for flexible behavior: unsupervised learning in a modular sensorimotor control architecture. Psychological Review, 114, 1015-1046. doi: 10.1037/0033-295X.114.4.1015

Butz, M. V., Goldberg, D. E., Lanzi, P.  L., & Sastry, K. (2007). Problem solution sustenance in XCS: Markov chain analysis of niche support distributions and consequent computational complexity. Genetic Programming and Evolvable Machines, 8, 5-37. doi: 10.1007/s10710-006-9012-8

Hoffmann, J., Berner, M., Butz, M. V., Herbort, O., Kiesel, A., Kunde, W., & Lenhard, A. (2007). Explorations of anticipatory behavioral control (ABC): A report from the cognitive psychology unit of the University of Würzburg. Cognitive Processing, 8, 133-142. doi: 10.1007/s10339-007-0166-y

Hoffmann, J., Butz, M. V., Herbort, O., Kiesel, A., & Lenhard, A. (2007). Spekulationen zur Struktur ideo-motorischer Beziehungen. Zeitschrift für Sportpsychologie, 14, 95-104. doi: 10.1026/1612-5010.14.3.95

2006

Butz, M. V., Pelikan, M., Llorà, X., & Goldberg, D. E. (2006). Automated global structure extraction for effective local building block processing in XCS. Evolutionary Computation, 14, 345-380. doi: 10.1162/evco.2006.14.3.345

2005

Butz, M. V., Goldberg, D. E., & Lanzi, P. L. (2005). Gradient descent methods in learning classifier systems: Improving XCS performance in multistep problems. IEEE Transactions on Evolutionary Computation, 9, 452-473. doi: 10.1109/TEVC.2005.850265

Butz, M. V., Sastry, K., & Goldberg, D. E. (2005). Strong, stable, and reliable fitness pressure in XCS due to tournament selection. Genetic Programming and Evolvable Machines, 6, 53-77. doi: 10.1007/s10710-005-7619-9

2004

Butz, M. V. (2004). Anticipation for learning, cognition, and education. On the Horizon, 12, 111-116. doi: 10.1108/10748120410555359

Butz, M. V., Kovacs, T., Lanzi, P. L., & Wilson, S. W. (2004). Toward a theory of generalization and learning in XCS. IEEE Transactions on Evolutionary Computation, 8, 28-46. doi: 10.1109/TEVC.2003.818194

2003

Butz, M. V., Goldberg, D. E., & Tharakunnel, K. (2003). Analysis and improvement of fitness exploitation in XCS: Bounding models, tournament selection, and bilateral accuracy. Evolutionary Computation, 11, 239-277. doi: 101162/106365603322365298

2002

Butz, M. V., Goldberg, D. E., & Stolzmann, W. (2002). The anticipatory classifier system and genetic generalization. Natural Computing, 1, 427-467. doi: 10.1023/A:1021330114221

Butz, M. V., & Hoffmann, J. (2002). Anticipations control behavior: Animal behavior in an anticipatory learning classifier system. Adaptive Behavior, 10, 75-96. doi: 10.1177/1059712302010002001

Butz, M. V., & Wilson, S. W. (2002). An algorithmic description of XCS. Soft Computing, 6, 144-153. doi: 10.1007/s005000100111

 


Conference Papers, Workshop Papers, & Book Chapters


2017

Butz, M. V. (2017). Which Structures Are Out There? - Learning Predictive Compositional Concepts Based on Social Sensorimotor Explorations. In T. Metzinger & W. Wiese (Eds.). Philosophy and Predictive Processing: 8. Frankfurt am Main: MIND Group. doi: 10.15502/9783958573093

Gumbsch, C., Otte, S., Butz, M. V. (2017). A Computational Model for the Dynamical of Event Taxonomies. Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 452 - 457.

Tsarava, K., Moeller, K., Pinkwart, N., Butz, M. V., Trautwein, U., & Ninaus, M. (2017). Training Computational Thinking: Game-Based Unplugged and Plugged-in Activities in Primary School. Proceedings of The 11th European Conference on Game-Based Learning ECGBL 2017.

 

2016

Butz, M. V., & Zöllner, D. (2016). Towards grounding compositional concept structures in self-organizing neural encodings. In: Proceedings in Language and Cognition 1, Sensory Motor Concepts in Language & Cognition, ed. L. Ströbel, (pp 177-192). Düsseldorf: Düsseldorf university press.

Kloss, A., Kappler, D., Lensch, H. P. A., Butz, M. V., Schaal, S., & Blog, J. (2016). Learning where to search using visual attention. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 5238-5245, doi: 10.1109/IROS.2016.7759770

Seth, A. K., Verschure, P. F. M. J., Blanke, O., Butz, M. V., Ford, J. M., Frith, Ch. D., Jacob, P., Kyselo, M., McGann, M., Menary, R., Morsella, E., & O'Regan, J. K. (2016): Action-oriented understanding of consciousness and the structure of experience. In A. K. Engel, K. J. Friston, & D. Kragic (Eds.), The Pragmatic Turn: Toward Action-Oriented Views in Cognitive Science, Strüngmann Forum Reports, vol. 18, J. Lupp, series editor, (pp 261-281). Cambridge, MA: MIT Press, 2016.

2015

Belardinelli, A., & Butz, M. V. (2015). It’s all in the eye: multiple orders of motor planning in gaze control. Proceedings of the 37th Annual Conference of the Cognitive Science Society, 2851.

Butz, M. V. (2015). Learning classifier systems. In J. Kacprzyk & W. Pedrycz (Eds.) Springer Handbook of Computation Intelligence, (pp. 961-981). Berlin: Springer-Verlag.

Butz, M. V., Geirhos, R., & Kneissler, J. (2015): An automatized Heider-Simmel Story generation tool. In D. C. Noelle, R. Cale, A. S. Warlaumont, J. Yoshimi, T. Mtlock, C. D Jennigs, & P. P. Maglio (Eds). (2015). Proceedings of the 37th Annual Conference of the Cognitive Science Society: Vol. 2861

2014

Belardinelli, A.,  Butz, M. V (Eds.) (2014). Proceedings of the 12th biannual conference of the German cognitive science society. Cognitive Processing 15, Supp. 1, 1-158.

Belardinelli, A., Kurz, J. M., Kutter, E. F., Neumann, H., Karnath, H. O., & Butz, M. V. (2014). Modeling simultanagnosia. Proceedings of the 36th Annual Conference of the Cognitive Science Society, 1911 - 1916.

Ehrenfeld, S., & Butz, M. V. (2014). An embodied kinematic model for perspective taking. Proceedings of the 12th Biannual Conference of the German Cognitive Science Society (KogWis2014), Suppl. 1, 97-100.

Kneissler, J., & Butz, M. V..(2014). Learning spatial transformations using structured gain-field networks. Prodeedings of the International Conference on Artificial Neural Networks (ICANN 2014), 683-690.

Lohmann, J., & Butz, M. V. (2014). Memory disclosed by motion: predicting visual working memory performance from movement patterns. Proceedings of the 12th Biannual Conference of the German Cognitive Science Society (KogWis 2014), Suppl. 1, 52-53.

Schrodt, F., & Butz, M. V. (2014). Modeling perspective-taking by forecasting 3D biological motion sequences. Proceedings of the 12th Biannual Conference of the German Cognitive Science Society (KogWis 2014), Suppl. 1, 137-139.

Schrodt, F., Layher, G., Neumann, H., & Butz, M. V. (2014). Modeling perspective-taking by correlating visual and proprioceptive dynamics. Proceedings of the 36th Annual Conference of the Cognitive Science Society (CogSci 2014), 1383-1388, 

Schrodt, F., Layher, G., Neumann, H., & Butz, M. V. (2014). Modeling perspective-taking upon observation of 3D biological motion. ICDL EpiRob Proceedings, 328-333.

2013

Alin, A., Fritsch, J., & Butz, M. V. (2013). Improved tracking and behavior anticipation by combining street map information with Bayesian filtering. International Conference on Intelligent Transportation Systems, IEEE 2013, pp. 2235-2242.

Belardinelli, A., & Butz, M. V. (2013). Gaze strategies in object identification and manipulation. Proceedings of the 35th annual meeting of the Cognitive Science Society CogSci 2013, 1875-1880.

Butz, M. V. (2013). Motivation. In A. Stephan, & S. Walter (Eds.), Handbuch Kognitionswissenschaft, (pp. 365-373). Stuttgart: J. B. Metzler.

Butz, M. V., Gufler, A., Schmid, K., & Schrodt, F. (2013). Fully self-supervised learning of an arm model. LWA Lernen, Wissen & Adaptivität 2013, Workshop Proceedings, pp. 184-190.

Cowling, P. I, Buro, M., Bida, M., Botea, B., Bouzy, B., Butz, M. V., Hingston, P., Munoz-Avila, H., Nau, D., & Sipper, M. (2013). Search in real-time video games. In S. M. Lucas, M. Mateas, M. Preuss, P. Spronck, & J. Togelius. (Eds.), Artificial and Computational Intelligence in Games (pp. 1-19). Retrieved from www.dagstuhl.de/dagpub/978-3-939897-62-0

Ehrenfeld, S., Herbort, O., & Butz, M. V. (2013). On modular, multimodal arm control models. In G. Baldassarre,  & M. Mirolli (Eds.), Computational and Robotic Models of the Hierarchical Organization of Behavior, Berlin Heidelberg: Springer.

Lohmann, J., & Butz, M. V. (2013). Modeling continuous representations in visual working memory. The Annual Meeting of the Cognitive Science Society, CogSci 2013, 2926-2931.

2012

Alin, A., Butz, M. V., & Fritsch, J. (2012). Incorporating Environmental Knowledge into Bayesian Filtering using Attractor Functions. IEEE Intelligent Vehicles Symposium (IV), pp. 476-481. doi:10.1109/IVS.2012.6232193

Butz, M.V., & Pezzulo, G. (2012). Anticipatory learning. In N. M. Seel (Ed.), Encyclopedia of the Sciences of Learning, (pp. 263-266), Berlin Heidelberg: Springer.

Droniou, A., Ivaldi, S., Stalph, P. O., Butz, M., & Sigaud, O. (2012). Learning velocity kinematics: Experimental comparison of on-line regression algorithms. 12th International Conference on Autonomous Robot Systems and Competitions, Robotica 2012, 15-20.
Ehrenfeld, S., & Butz, M.V. (2012). Autonomous failure detection and multimodal sensor fusion in a modular arm model. IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012, 2186-2191.

Kneissler, J., Stalph, P. O., Drugowitsch, J., & Butz, M. V. (2012). Filtering sensory information with XCSF. Improving learning robustness and control performance. Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, ACM, 871-878.

Koryakin, D., & Butz, M. V. (2012). Reservoir sizes and feedback weights interact non-linearly in echo state networks. ICANN International Conference on Artificial Neural Networks, 499-506, Berlin Heidelberg: Springer.

Lohmann, J., Herbort, O., & Butz, M. V. (2012). Modeling the temporal dynamics of visual working memory. International Conference on Cognitive Modeling (ICCM 2012). www.iccm2012.com/proceedings/papers/0044/index.html

Pezzulo, G., & Butz, M. V. (2012). Schema-based architectures of machine learning. In N. M. Seel (Ed.), Encyclopedia of the Sciences of Learning, (2942-2945), Berlin Heidelberg: Springer.

Stalph, P. O., & Butz, M. V. (2012). Guided Evolution in XCSF. Conference on Genetic and Evolutionary Computation, ACM,  911-918.

2011

Alin, A., Butz, M. V., & Fritsch, J. (2011). Tracking moving vehicles using an advanced drid-based Bayesian filter approach. IEEE Intelligent Vehicles Symposium (IV), 466-472.

Butz, M. V. (2011). Towards Grounding Language in Self-organized Neural Encodings. Sensory-Motor Concepts in Language and Cognition. SMCLC 2011. http://www.sfb991.uni-duesseldorf.de/smclc11.

Butz, M. V., & Sigaud, O. (2011). XCSF with local deletion: Preventing detrimental forgetting. Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, ACM, 383-390.

Butz, M. V., & Stalph, P. O. (2011). Modularization of XCSF for multiple output dimensions. Proceedings of the 13th annual conference on Genetic and evolutionary computation, ACM, 1243-1250.

Butz, M. V. (2011) Extracting adaptation strategies for e-learning programs with XCS. Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, ACM, 743-746.

Ehrenfeld, S., & Butz, M. V. (2011). A modular, redundant, multi-frame of reference representation for kinematic chains. IEEE International Conference on Robotics and Automation, ICRA 2011, 141-147.

Lohmann, J. & Butz, M. V. (2011). Learning a neural multimodal body schema: Linking vision with proprioception. In B. Hammer,  & T. Villmann, Workshop New Challenges in Neural Computation 2011, University of Bielefeld, Dept. of Technology CITEC, pp. 53-57.

2010

Butz, M. V. (2010). Curiosity in learning sensorimotor maps. In J. Haack, H. Wiese, A. Abraham, & C. Chiarcos (Eds.). KogWis 2010 - 10. Tagung der Gesellschaft für Kognitionswissenschaft (p.92). Potsdam Cognitive Science Series 2.

Herbort, O., & Butz, M. V. (2010). The continuous endstate comfort effect: The impact of contextual, motor and cognitive factors. 51st Annual Meeting of the Psychonomic Society.
Herbort, O., Butz, M. V., & Pedersen G. (2010).  The SURE REACH model for motor learning and control of a redundant arm: From modeling human behavior to applications in robots. In J. Peters and O. Sigaud (Eds.), From motor to interaction learning in robots (pp. 85-106). Berlin Heidelberg: Springer.

Pedersen, G .K. M., & Butz, M. V. (2010). Evolving robust controller parameters using CMA. Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, ACM, (pp. 1251-1258).

Pedersen, G. K. M., & Butz, M. V. (2010). Parameter investigation of muscle-like actuators. 1st International Conference on Applied Bionics and Biomechanics. ICABB-2010.

Stalph, P.O., & Butz, M. V. (2010). Current XCSF capabilities and challenges. In J. Bacardit, J. Drugowitsch, W. Browne, E. Bernadó-Mansilla, & M.V. Butz (Eds.), Learning classifier systems, LNCS 6471 (pp 57-69). Berlin Heidelberg: Springer.

Stalph, P. O., & Butz, M. V. (2010). How fitness estimates interact with reproduction rates: Towards variable offspring set sizes in XCSF. In J. Bacardit, J. Drugowitsch, W. Browne, E. Bernadó-Mansilla, & M.V. Butz (Eds.), Learning classifier systems, LNCS 6471 (pp 47-56). Berlin Heidelberg: Springer.

Stalph, P. O., Rubinsztajn, J., Sigaud, O, & Butz, M. V. (2010). A comparative study: Function approximation with LWPR and XCSF. Genetic and Evolutionary Computation Conference, GECCO 2010, IWLCS Workshop Proceedings (pp. 1863-1870).

Sugita, Y, & Butz, M. V. (2010). Towards emergent strong systematicity in a simple dynamical connectionist network. CONAS: Cognitive and Neural Models for Automated Processing of Speech and Text. http://conas.elis.ugent.be.

2009

Butz, M. V. (2009). Sensorimotor self-motivated cognition. In U. Schmid, M. Ragni, & M. Knauff (Eds.). Workshop on Complex Cognition. 32nd Annual Conference on Artificial Intelligence, KI 2009, Workshop Proceedings.

Butz, M. V., & Lönneker, T. (2009). Optimized sensory-motor couplings plus strategy extensions for the TORCS car racing challenge. IEEE Symposium on Computational Intelligence in Games, IEEE CIG 2009, 317-324.
Butz, M. V., & Pedersen, G. K. M. (2009). The scared robot: Motivations in a simulated robot arm. 32nd Annual Conference on Artificial Intelligence, KI 2009, 460-467.
Butz, M. V., Pedersen, G. K. M., & Stalph, P. O. (2009). Learning sensorimotor control structures with XCSF: Redundancy exploitation and dynamic control. Genetic and Evolutionary Computation Conference, GECCO 2009, 1171-1178.
Linhardt, M. J., & Butz, M. V. (2009). NEAT in increasingly non-linear control situations. Genetic and Evolutionary Computation Conference, GECCO 2009, 2091-2095.

Lohmann, J., Herbort, O., Wagener, A., & Kiesel, A. (2009). Anticipations of time spans: New data from the foreperiod paradigm and the adaptation of a computational model. In G. Pezzulo, M. V. Butz, O. Sigaud, G. Baldassarre (Eds.), Anticipatory Behavior in Adaptive Learning Systems: From Psychological Theories to Artificial Cognitive Systems (pp. 170-187). Berlin, Heidelberg: Springer. (book website).

Pelikan, M., Sastry, K., Goldberg, D. E., Butz, M. V., & Hauschild, M. (2009). Performance of evolutionary algorithms on NK landscapes with nearest neighbor interactions and tunable overlap. Genetic and Evolutionary Computation Conference, GECCO 2009, 851-858.
Pezzulo, G., Butz, M. V., Sigaud, O., & Baldassarre, G. (2009). From sensorimotor to higher-level cognitive processes: An introduction to anticipatory behavior systems. In G. Pezzulo, M. V. Butz, O. Sigaud, & G. Baldassarre (Eds.), Anticipatory Behavior in Adaptive Learning Systems: From Psychological Theories to Artificial Cognitive Systems, LNAI 5499, (pp 1-9). Berlin Heidelberg: Springer.
Sigaud, O., Butz, M. V., Kozlova, O., & Meyer, C. (2009). Anticipatory learning classifier systems and factored reinforcement learning. In G.Pezzulo, M. V. Butz, O. Sigaud, & G. Baldassarre (Eds.) Anticipatory Behavior in Adaptive Learning Systems: From Psychological Theories to Artificial Cognitive Systems, LNAI 5499, (pp. 321-333).  Berlin Heidelberg: Springer.
Stalph, P. O., Butz, M. V., Goldberg, D. E., & Llorà, X. (2009). On the scalability of XCS(F). Genetic and Evolutionary Computation Conference, GECCO 2009, 1315-1322.
Stalph, P. O., Butz, M. V., & Pedersen, G. K. M. (2009). Controlling a four degree of freedom arm in 3D using XCSF. 32nd Annual Conference on Artificial Intelligence, KI 2009, 193-200.
Shirinov, E., & Butz, M. V. (2009). Distinction between types of motivations: Emergent behavior with a neural, model-based reinforcement learning system. 2009 IEEE Symposium Series on Artificial Life (ALIFE 2009) Proceedings, 69-76.

2008

Bacardit, J., Bernadó-Mansilla, E., & Butz, M. V. (2008). Learning classifier systems: Looking back and glimpsing ahead. In J. Bacardit, E. Bernadó-Mansilla, E., M. V. Butz, T.Kovacs, X. Llorà, & K. Takadama (Eds.) Learning Classifier Systems, LNAI 4998, (pp. 1-21). Berlin Heidelberg: Springer

Butz, M. V., Herbort, O., & Pezzulo, G. (2008). Anticipatory, goal-directed behavior. In G. Pezzulo, M. V.  Butz, C. Castelfranchi,  & R. Falcone (Eds.) The Challenge of Anticipation: A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems, LNAI 5225 (pp. 85-114).  Berlin Heidelberg: Springer.
(References)
Butz, M. V., & Pezzulo, G. (2008). Benefits of anticipations in cognitive agents. In G. Pezzulo, M. V. Butz, C. Castelfranchi, & R. Falcone (Eds.) The Challenge of Anticipation: A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems, LNAI 5225 (pp. 45-62). Berlin Heidelberg:Springer.
(References)

Butz, M. V., & Herbort, O. (2008). Context-dependent predictions and cognitive arm control with XCSF. GECCO 2008: Genetic and Evolutionary Computation Conference, 1357-1364 (best paper award).

Butz, M. V., Lanzi, P. L., Llorà, X., & Loiacono, D. (2008). An analysis of matching in learning classifier systems. GECCO 2008: Genetic and Evolutionary Computation Conference, 1349-1356.

Butz, M. V., Reif, K., & Herbort, O. (2008). Bridging the gap: Learning sensorimotor-linked population codes for planning and motor control. International Conference on Cognitive Systems (CogSys 2008), 123-129.

Butz, M. V., Stalph, P., & Lanzi, P. L. (2008). Self-adaptive mutation in XCSF. GECCO 2008: Genetic and Evolutionary Computation Conference, 1365-1372.

Herbort, O., Butz, M. V., & Hoffmann, J. (2008). Multimodal goal representations and feedback in hierarchical motor control. International Conference on Cognitive Systems (CogSys 2008).

Klügl, F., Hatko, R., & Butz, M. V. (2008). Agent learning instead of behavior implementation for simulations ? A case study using classifier systems. 6th German Conference on Multi-Agent System Technologies, MATES 2008, 111-122.

Pezzulo, G., Butz, M.V., & Castelfranchi, C. (2008). The anticipatory approach: Definitions and taxonomies. In Pezzulo, G., Butz, M.V., Castelfranchi, C., & Falcone, R. (Eds.) The challenge of anticipation: A unifying framework for the analysis and design of artificial cognitive systems, LNAI 5225, Springer-Verlag, Berlin Heidelberg, 23-43.
(References)

Pezzulo, G., Butz, M. V., Castelfranchi, C., & Falcone, R. (2008). Introduction: Anticipation in natural and artificial cognition. In G. Pezzulo, M. V. Butz, C. Castelfranchi, & R. Falcone, R. (Eds.) The challenge of anticipation: A unifying framework for the analysis and design of artificial cognitive systems, LNAI 5225 (pp. 3-22). Berlin Heidelberg: Springer.
(References)

Pezzulo, G., Butz, M. V., Castelfranchi, C., Falcone, R., Baldassarre, G., Balkenius, C., Förster, A., Grinberg, M., Herbort, O., Kiryazov, K., Kokinov, B., Johansson, B., Lalev, E., Lorini, E., Martinho, C., Miceli, M., Ognibene, D., Paiva, A., Petkov, G., Piunti, M., & Thorsteinsdottir, V. (2008). Endowing artificial systems with anticipatory capabilities: Success cases. In G. Pezzulo, M. V. Butz, C. Castelfranchi,  & R. Falcone (Eds.) The Challenge of Anticipation: A unifying framework for the analysis and design of artificial cognitive systems, LNAI 5225 (pp. 237-254). Berlin Heidelberg: Springer.
(References)

Stalph, P., & Butz, M. V. (2008). Towards increasing learning speed and robustness of XCSF: Experimenting with larger offspring set sizes. GECCO 2008: Genetic and Evolutionary Computation Conference, Workshop Proceedings IWLCS 2008, 2023-2029.

2007

Bacardit, J., & Butz, M. V. (2007). Data mining in learning classifier systems: Comparing XCS with GAssist. In Kovacs, T., Llorà, X., Takadama, K., Lanzi, P. L., Stolzmann, W., & Wilson, S. W. (Eds.) Learning Classifier Systems: International Workshops, IWLCS 2003-2005, LNAI 4399 (pp. 282-290). Berlin Heidelberg: Springer.

Bacardit, J., Goldberg, D. E., & Butz, M. V. (2007). Improving the performance of a Pittsburgh learning classifier system using a default rule. In T. Kovacs, T., Llorà, X., Takadama, K., Lanzi, P.L., Stolzmann, W., & Wilson, S.W. (Eds.) Learning Classifier Systems: International Workshops, IWLCS 2003-2005, LNAI 4399 (pp. 291-307). Berlin Heidelberg: Springer.

Butz, M. V. (2007). Combining gradient-based with evolutionary online learning: An introduction to learning classifier systems. Seventh International Conference on Hybrid Intelligent Systems (HIS 2007), 12-17.

Butz, M. V. (2007). Documentation of XCSFJava 1.1 plus visualization. Missouri Estimation of Distribution Algorithms Laboratory, MEDAL Report No. 2007008.

Butz, M. V. (2007). The XCSF classifier system in Java. SIGEVOlution, 2, 2, 10-13.

Butz, M. V., Goldberg, D.E., & Lanzi, P.L. (2007). Effect of pure error-based fitness in XCS. In Kovacs, T., Llorà, X., Takadama, K., Lanzi, P.L., Stolzmann, W., & Wilson, S.W. (Eds.) Learning classifier systems: International Workshops, IWLCS 2003-2005, LNAI 4399 (pp. 104-114). Berlin Heidelberg: Springer.

Butz, M. V., Lenhard, A., & Herbort, O. (2007). Emergent effector-independent internal spaces: Adaptation and intermanual learning transfer in humans and neural networks. International Joint Conference on Neural Networks (IJCNN 2007). 1509-1514.

Butz, M. V., Sigaud, O., Pezzulo, G., & Baldassarre, G. (2007). Anticipations, brains, individual and social behavior: An introduction to anticipatory systems. In M. V. Butz, O. Sigaud, G. Pezzulo, & G. Baldassarre (Eds.), Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior. LNAI 4520 (pp. 1-18), Berlin Heidelberg: Springer.

Herbort, O., & Butz, M. V. (2007). Encoding complete body models enables task dependent optimal behavior. International Joint Conference on Neural Networks (IJCNN 2007). 1424-1429.

Herbort, O., Ognibene, O., Butz, M. V., & Baldassarre, G. (2007). Learning to select targets within targets in reaching tasks. The 6th IEEE International Conference on Development and Learning (ICDL2007), 7-12.

Lanzi, P. L., Butz, M. V., & Goldberg, D. E. (2007). Empirical analysis of generalization and learning in XCS with gradient descent. GECCO 2007: Genetic and Evolutionary Computation Conference. 1814-1821.

Pezzulo, G., Baldassarre, G., Butz, M. V., Castelfranchi, C., & Hoffmann, J. (2007). From actions to goals and vice-versa: Theoretical analysis and models of the ideomotor principle and TOTE. In M. V. Butz, O. Sigaud, G. Pezzulo,  & G. Baldassarre, G. (Eds.), Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior. LNAI 4520 (pp. 73-93), Berlin Heidelberg: Springer.

2006

Butz, M. V., Lanzi, P.  L., & Wilson, S. W. (2006). Hyper-ellipsoidal conditions in XCS: Rotation, linear approximation, and solution structure. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2006), 1457-1464.

Butz, M. V., & Pelikan, M. (2006). Studying XCS/BOA learning in Boolean functions: Structure encoding and random Boolean functions. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2006), 1449-1456.

Lima, C. F., Pelikan, M., Sastry, K., Butz, M. V., Goldberg, D. E., & Lobo, F. G. (2006). Substructural neighborhoods for local search in the Bayesian optimization algorithm. Parallel Problem Solving from Nature - PPSN IX, 232-241.

Pelikan, M., Sastry, K., Butz, M. V., & Goldberg, D. E. (2006). Performance of evolutionary algorithms on random decomposable problems. Parallel Problem Solving from Nature - PPSN IX, 788-797.

Pezzulo, G., Baldassarre, G., Butz, M. V., Castelfranchi, C., & Hoffmann, J. (2006). An analysis of the ideomotor principle and TOTE. In M. V. Butz, O. Sigaud, G. Pezzulo, & G. Baldassarre (Eds.) Proceedings of the Third Workshop on Anticipatory Behavior in Adaptive Learning Systems (ABiALS 2006).

2005

Butz, M. V. (2005). Kernel-based, ellipsoidal conditions in the real-valued XCS classifier system. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2005), 1835-1842.

Butz, M. V., Goldberg, D. E., & Lanzi, P. L. (2005). Computational complexity of the XCS classifier system. In L Bull, & T. Kovacs (Eds.) Foundations of Learning Classifier Systems, 91-126.

Butz, M. V., Pelikan, M., Llorà, X., & Goldberg, D. E. (2005). Extracted global structure makes local building block processing effective in XCS. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2005), 655-662.

Herbort, O., Butz, M. V., & Hoffmann, J. (2005). Towards an adaptive hierarchical anticipatory behavioral control system. In C. Castelfranchi, C. Balkenius, M. V. Butz, & A. Ortony (Eds.) From Reactive to Anticipatory Cognitive Embodied Systems: Papers from the AAAI Fall Symposium, AAAI Press, 2005, 83-90.

Herbort, O., Butz, M. V., & Hoffmann, J. (2005). Towards the advantages of hierarchical anticipatory behavioral control. In K. Opwis, & I. Penner (Eds.) Proceedings of the KogWis05. The German Cognitive Science Conference, Schwabe, 2005, 77.

2004

Bacardit, J., Goldberg, D. E., Butz, M. V., Llorà, X., & Garrell, J. M. (2004). Speeding-up Pittsburgh learning classifier systems: Modelling time and accuracy. Parallel Problem Solving from Nature - PPSN VIII, LNCS 3242, 1021-1031.

Butz, M. V., Goldberg, D. E., & Lanzi, P. L. (2004). Bounding learning time in XCS. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004), LNCS 3103, 739-750.

Butz, M. V., Goldberg, D. E., & Lanzi, P. L. (2004). Gradient-based learning updates improve XCS performance in multistep problems. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004), LNCS 3103, 751-762.

Butz, M. V., Lanzi, P. L., Llorà, X., & Goldberg, D. E. (2004). Knowledge extraction and problem structure identification in XCS. Parallel Problem Solving from Nature - PPSN VIII, 8th International Conference, LNCS 3242, 1051-1060.

Butz, M. V., Swarup, S., & Goldberg, D. E. (2004). Effective online detection of task-independent landmarks. Online Proceedings for the ICML'04 Workshop on Predictive Representations of World Knowledge.

2003

Butz, M. V., & Goldberg, D. E. (2003). Bounding the population size in XCS to ensure reproductive opportunities. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003). LNCS 2724, 1844-1856.

Butz, M.V., & Ray, S. (2003). Bidirectional ARTMAP: An artificial mirror neuron system. Proceedings of the International Joint Conference on Artificial Neural Networks (IJCNN 2003). 1417-1422.

Butz, M. V., Sastry, K., & Goldberg, D. E. (2003). Tournament selection in XCS. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003). LNCS 2724, 1857-1869. (Best paper award)

Tharakunnel, K., Butz, M. V., & Goldberg, D. E. (2003). Towards building block propagation in XCS: A negative result and its implications. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003). LNCS 2724, 1906-1917.

2002

Butz, M. V. (2002). Biasing exploration in an anticipatory learning classifier system. In P. L. Lanzi, W. Stolzmann, & S. W. Wilson (Eds.) Advances in Learning Classifier Systems: Fourth International Workshop (IWLCS 2001), LNAI 2321 (pp. 3-22). Berlin Heidelberg: Springer.

Butz, M. V., & Goldberg, D. E. (2002). Generalized state values in an anticipatory learning classifier system. Seventh International Conference on Simulation of Adaptive Behavior: From animals to animats. Adaptive Behavior in Anticipatory Learning Systems Workshop Proceedings. 78-96.

Butz, M. V., Sigaud, O., & Gérard, P. (2002). Internal models and anticipations in adaptive learning systems. Seventh International Conference on Simulation of Adaptive Behavior: From animals to animats. Adaptive Behavior in Anticipatory Learning Systems Workshop Proceedings. 1-20.

Butz, M. V., & Stolzmann, W. (2002). An algorithmic description of ACS2. In P. L. Lanzi, W. Stolzmann, & S. W. Wilson (Eds.) Advances in Learning Classifier Systems: Fourth International Workshop (IWLCS 2001), LNAI 2321 (pp. 211-230). Berlin Heidelberg: Springer.

2001

Butz, M. V., Goldberg, D. E., & Stolzmann, W. (2001). Probability-enhanced predictions in the anticipatory classifier system. In P. L. Lanzi, W. Stolzmann, & S. W. Wilson (Eds.) Advances in Learning Classifier Systems: Third International Workshop (IWLCS 2000), LNAI 1996 (pp. 37-52). Berlin Heidelberg: Springer.

Butz, M. V., Kovacs, T., Lanzi, P. L., & Wilson, S. W. (2001). How XCS evolves accurate classifiers. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), 927-934

Butz, M. V., & Pelikan, M. (2001). Analyzing the evolutionary pressures in XCS. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), 935-942.

Butz, M. V., & Wilson, S. W. (2001). An algorithmic description of XCS. In Lanzi, P.L., Stolzmann, W., & Wilson, S.W. (Eds.) Advances in Learning Classifier Systems: Third International Workshop (IWLCS 2000), LNAI 1996 (pp. 253-272). Berlin Heidelberg: Springer.

2000

Butz, M. V., Goldberg, D. E., & Stolzmann, W. (2000). Introducing a genetic generalization pressure to the anticipatory classifier system: Part 1 - theoretical approach. Proceedings of the Second Genetic and Evolutionary Computation Conference (GECCO-2000), 34-41.

Butz, M. V., Goldberg, D. E., & Stolzmann, W. (2000). Introducing a genetic generalization pressure to the anticipatory classifier system: Part 2 - performance analysis. Proceedings of the Second Genetic and Evolutionary Computation Conference (GECCO-2000), 42-49.

Butz, M. V., Goldberg, D. E., & Stolzmann, W. (2000). Investigating genetic generalization in the anticipatory classifier system. Parallel problem solving from nature (PPSN VI), 735-744.

Stolzmann, W., & Butz, M. V. (2000). Latent learning and action planning in robots with anticipatory classifier systems. In Lanzi, P.L., Stolzmann, W., & Wilson, S.W. (Eds.) Learning Classifier Systems: From Foundations to Applications, LNAI 1813 (pp. 301-317). Berlin Heidelberg: Springer.

Stolzmann, W., Butz, M. V., Hoffmann, J., & Goldberg, D. E. (2000). First cognitive capabilities in the anticipatory classifier system. Sixth International Conference on Simulation of Adaptive Behavior: From animals to animats. (SAB VI), 287-296.

1999

Butz, M. V., & Stolzmann, W. (1999). Action-planning in anticipatory learning classifier systems. 2nd International Workshop on Learning Classifier Systems (IWLCS-99). Genetic and Evolutionary Computation Conference (GECCO 1999) Workshop Program, 242-249.

 


Books


 

Butz, M. V., & Kutter, E. F. (2016). How the mind comes into being: Introducing Cognitive Science from a functional and computational perspective. Oxford University Press

 

Bacardit, J., Browne, W., Drugowitsch, J., Bernadó-Mansilla, E., & Butz, M. V. (Eds.) (2010). Learning classifier systems: 11th international workshop, IWLCS 2008, Atlanta, GA, USA, July 13, 2008 and 12th international workshop, IWLCS 2009 Montreal, QC, Canada, July 9, 2009 revised selected papers, LNCS 6471. Berlin Heidelberg: Springer.

 

Pezzulo, G., Butz, M. V., Sigaud, O., & Baldassarre G. (Eds.) (2009). Anticipatory Behavior in Adaptive Learning Systems: From Psychological Theories to Artificial Cognitive Systems, LNAI 5499 (State-of-the-Art Survey). Berlin Heidelberg: Springer.

 

Bacardit, J., Bernadó-Mansilla, E., Butz, M. V., Kovacs, T., Llorà, X., & Takadama, K. (Eds.) (2008). Learning Classifier Systems:10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 2007 Revised Selected Papers, LNAI 4998. Berlin Heidelberg: Springer.

 

Pezzulo, G., Butz, M. V., Castelfranchi, C. & Falcone, R. (Eds.) (2008). The Challenge of Anticipation: A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems, LNAI 5225 (State-of-the-Art Survey). Berlin Heidelberg: Springer.

 

Butz, M. V., Sigaud, O., Pezzulo, G., & Baldassarre, G. (Eds.) (2007). Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior, LNAI 4520 (State-of-the-Art Survey). Berlin-Heidelberg: Springer.

 

Butz, M. V. (2006). Rule-based evolutionary online learning systems: A principled approach to LCS analysis and design. Studies in Fuzziness and Soft Computing Series. Berlin Heidelberg: Springer.

 

Keijzer, M., Cattolico, M., Arnold, D., Babovic, V., Blum, C., Bosman, P., Butz, M. V., Coello Coello, C., Dasgupta, D., Ficici, S. G., Foster, J., Hernandez-Aguirre, A., Hornby, G., Lipson, H., McMinn, P., Moore, J., Raidl, G., Rothlauf, F., Ryan, C., & Thierens, D. (Eds.) (2006). GECCO: Proceedings of the 8th annual conference on genetic and evolutionary computation. Seattle, WA, USA: ACM Press.

 

Butz, M. V., Sigaud, O., & Gerard, P. (Eds.). (2003). Anticipatory Behavior in Adaptive Learning Systems: Foundations, Theories, and Systems, LNAI 2684 (State-of-the-Art Survey). Berlin Heidelberg: Springer.

 

Butz, M. V. (2002). Anticipatory learning classifier systems. Boston, MA: Kluwer Academic Publishers.