Improving XCS performance by distribution

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5361 LNAI, Issue , 2008, Pages 111-120

  Richter, Urban ^a   Prothmann, Holger ^a   Schmeck, Hartmut ^a  

^a KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIERS; LEARNING SYSTEMS; REINFORCEMENT;

LEARNING CLASSIFIER SYSTEMS; LEARNING SPEEDS; LEARNING TASKS; MACHINE LEARNINGS; MULTI AGENTS; WIDESPREAD APPLICATIONS;

EDUCATION;

EID: 58349096146     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-89694-4_12     Document Type: Conference Paper

References (13)

1. Richter, U., Mnif, M., Branke, J., Müller-Schloer, C., Schmeck, H.: Towards a generic observer/controller architecture for Organic Computing. In: INFORMATIK 2006 - Informatik für Menschen!, pp. 112-119. Köllen Verlag (2006)
2. Wilson, S.W.: Classifier fitness based on accuracy. Evolutionary Computation 3(2), 149-175 (1995)
3. Kovacs, T.: Learning classifier systems resources. Soft Computing 6(3-4), 240-243 (2002)
4. Dam, H.H., Abbass, H.A., Lokan, C.: Be real! XCS with continuous-valued inputs. In: Proceedings of the 2005 Workshops on Genetic and Evolutionary Computation (GECCO 2005), pp. 85-87. ACM, New York (2005)
5. Barry, A.: Hierarchy formation within classifier systems - A review. In: Proceedings of the 1st International Conference on Evolutionary Algorithms an their Applications (EVCA 1996), Moscow, pp. 195-211 (1996)
6. Baneamoon, S.M., Salam, R.A., Talib, A.Z.H.: Learning process enhancement for robot behaviors. Int. Journal of Intelligent Technology 2(3), 172-177 (2007)
7. Dorigo, M.: Alecsys and the autonomouse: Learning to control a real robot by distributed classifier systems. Machine Learning 19(3), 209-240 (1995)
8. Dam, H.H., Abbass, H.A., Lokan, C.: DXCS: An XCS system for distributed data mining. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2005), pp. 1883-1890. ACM, New York (2005)
9. Gershoff, M., Schulenburg, S.: Collective behavior based hierarchical XCS. In: Proceedings of the 2007 Genetic And Evolutionary Computation Conference (GECCO 2007), pp. 2695-2700. ACM, New York (2007)
10. Mnif, M., Richter, U., Branke, J., Schmeck, H., Müller-Schloer, C.: Measurement and control of self-organised behaviour in robot swarms. In: Lukowicz, P., Thiele, L., Tröster, G. (eds.) ARCS 2007. LNCS, vol. 4415, pp. 209-223. Springer, Heidelberg (2007)
11. Mnif, M., Müller-Schloer, C.: Quantitative emergence. In: Proceedings of the 2006 IEEE Mountain Workshop on Adaptive and Learning Systems (IEEE SMCals 2006), pp. 78-84 (July 2006)
12. Richter, U., Mnif, M.: Learning to control the emergent behaviour of a multi-agent system. In: Proceedings of the 2008 Workshop on Adaptive Learning Agents and Multi-Agent Systems at AAMAS 2008 (ALAMAS+ALAg 2008), pp. 33-40 (May 2008)
13. Butz, M.V.: XCSJava 1.0: An implementation of the XCS classifier system in Java. Technical Report 2000027, Illinois Genetic Algorithms Laboratory (2000)