%0 Book Section %1 kinnear:andrews %A Andrews, Martin %A Prager, Richard %B Advances in Genetic Programming %D 1994 %E Kinnear, Jr., Kenneth E. %I MIT Press %K algorithms, genetic programming %P 355--368 %T Genetic Programming for the Acquisition of Double Auction Market Strategies %U http://cognet.mit.edu/library/books/view?isbn=0262111888 %& 16

@incollection{kinnear:andrews, added-at = {2008-06-19T17:35:00.000+0200}, author = {Andrews, Martin and Prager, Richard}, biburl = {https://www.bibsonomy.org/bibtex/26ce79f895732b180db51ba3ea8099f7a/brazovayeye}, booktitle = {Advances in Genetic Programming}, chapter = 16, editor = {{Kinnear, Jr.}, Kenneth E.}, interhash = {07669613f83608423b6c1ee8a953e327}, intrahash = {6ce79f895732b180db51ba3ea8099f7a}, keywords = {algorithms, genetic programming}, notes = {{"} a GP approach was very successful in learning strategies for playing a simple game with complex dynamics{"} Ref Knobeln Contest: Sanfrancisco.ira.uka.de [129.13.13.110] /pub/knobeln Generational GP pop=300, touranment selection? size=2? Comparison with Simulated Annealing:SA also good but GP better Best GP exceeded performance of handcode routines (on average?) 65% of time. Check details of what exctly this means. Set number of games played so could distinquish meadian from top quartile with 95% confidence. Claims it helps, but doesnt seem to have either speeded things at lot or made much better result.}, pages = {355--368}, publisher = {MIT Press}, size = {14 pages}, timestamp = {2008-06-19T17:35:44.000+0200}, title = {Genetic Programming for the Acquisition of Double Auction Market Strategies}, url = {http://cognet.mit.edu/library/books/view?isbn=0262111888}, year = 1994 }