Evolutionary agent learning

References

• Bigus , J.P. , Schlosnagle , D.A. , Pilgrim , J.R. , Mills , W.N. III and Diao , Y. 2002 . ABLE: a toolkit for building multiagent autonomic systems . IBM Syst. J. , 41 ( 3 )
   Google Scholar
• Buczak , A.L. and Wang , H. 2001 . “ Optimization of fitness functions with non-ordered parameters by genetic algorithms ” . In Proceedings of the Congress on Evolutionary Computation Seoul, Korea
   Google Scholar
• Buczak , A.L. , Cooper , D.G. and Hofmann , M.O. 2003 . Evolutionary Platform for Agent Learning, Intelligent Engineering Systems Through Artificial Neural Networks , Edited by: Dagli , C.H. , Buczak , A.L. , Ghosh , J. , Embrechts , M.J. and Ersoy , O. Vol. 13 , 201 – 206 . New York, NY : ASME Press .
   Google Scholar
• Buczak , A.L. , Cooper , D.G. and Hofmann , M.O. 2004 . Advances in Evolutionary Agent Learning, Intelligent Engineering Systems Through Artificial Neural Networks , Edited by: Dagli , C.H. , Buczak , A.L. , Enke , D.L. , Embrechts , M.J. and Ersoy , O. Vol. 14 , 157 – 164 . New York, NY : ASME Press .
   Google Scholar
• ECJ, www.cs.umd.edu/projects/plus/ec/ecj/
   Google Scholar
• Fogarty , T.C. 1989 . “ Varying the probability of mutation in the genetic algorithm ” . In Proceedings of International Conference on Genetic Algorithms Edited by: Schaffer , J.D. 105 – 109 . George Mason University
   Google Scholar
• Hofmann , M.O. , Chacón , D. , Mayer , G. , Whitebread , K.R. and Hendler , J. 2001 . “ CAST agents: network-centric fires unleashed ” . In Proceedings of the 2001 National Fire Control Symposium Lihue, HI
   Google Scholar
• Hofmann , M.O. , McGovern , A. and Whitebread , K.R. 1998 . “ Mobile agents on the digital battlefield ” . In Proceedings of the Second International Conference on Autonomous Agents (Agents '98) 219 – 225 . Minneapolis/St Paul, May 10–13
   Google Scholar
• JSAF, 2000, Joint Semi Automated Forces, http://www.afmsrr.afams.af.mil/index.cfm?RID=MDL_AF_1000066
   Google Scholar
• Koza , J. 1992 . Genetic Programming—On the Programming of Computers by Means of Natural Selection , Massachusetts : MIT Press Cambridge .
   Google Scholar
• Koza , J. 1994 . Genetic Programming II , Massachusetts : MIT Press Cambridge .
   Google Scholar
• Montana , D. 1995 . Strongly typed genetic programming . Evol. Comput. , 3 ( 2 ) : 199 – 230 .
   Web of Science ®Google Scholar
• Ramamurthy , U. , Bogner , M. and Franklin , S. 1998 . “ Conscious learning in an adaptive software agent ” . In Proceedings of the Second Asia Pacific Conference on Simulated Evolution and Learning Canberra, Australia
   Google Scholar
• Srinivas , M. and Patnaik , L.M. 1994 . Adaptive probabilities of crossover and mutation in genetic algorithms . IEEE Trans. Syst. Man Cybern. , 24 ( 4 ) : 656 – 667 .
   Web of Science ®Google Scholar
• Spears , W. 1995 . “ Adapting crossover in evolutionary algorithms ” . In Proceedings of the Evolutionary Programming Conference Edited by: McDonell , J.R. , Reynolds , R.G. and Fogel , D.B. 367 – 384 . San Diego, CA
   Google Scholar
• K. Shaw, “Fast forward to the future”, http://www.janes.com/defence/naval_forces/news/jni/jni020917_1_ n.shtml , 2002.
   Google Scholar
• S. Gallup, G. Schacher, J. Jensen, S. Saylor and J. Tangorra, “Fleet battle experiment Juliet final reconstruction and analysis report”, Report number A279514, http://www.stormingmedia.us/27/2795/A279514.htm (http://www.stormingmedia.us/27/2795/ a279514.htm) , 2003.
   Google Scholar
• Simon , H.A. 1989 . “ Models of thought ” . In Learning Processes Vol. II , 99 – 184 . Chapter 3, Yale University
   Google Scholar
• P. Stone, “Layered learning in multi-agent systems”, PhD thesis, Carnegie Mellon University, 1998.
   Google Scholar
• Sun , R. , Merrill , E. and Peterson , T. 2001 . From implicit to explicit knowledge: a bottom-up model of skill learning . Cogn. Sci. , 25 ( 2 ) : 203 – 244 .
   Web of Science ®Google Scholar
• Sutton , R. 1990 . “ Integrated architectures for learning, planning, and reacting based on approximating dynamic programming ” . In Proceedings of Seventh International Conference on Machine Learning 216 – 224 . San Mateo, CA
   Google Scholar
• Wagman , M. 1991 . Cognitive Science and Concepts of Mind Toward a General Theory of Human and Artificial Intelligence , New York, NY : Praeger .
   Google Scholar