Thu, 21 Aug 2008 00:46:17 BST CiteULike: mcphee's tag http://www.citeulike.org/user/mcphee/tag/tag CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/mcphee/article/2374194 <i>Evolutionary Computation, IEEE Transactions on, Vol. 10, No. 2. (2006), pp. 157-166.</i><br /><br />Standard tree-based genetic programming suffers from a structural difficulty problem in that it is unable to search effectively for solutions requiring very full or very narrow trees. This deficiency has been variously explained as a consequence of restrictions imposed by the tree structure or as a result of the numerical distribution of tree shapes. We show that by using a different tree-based representation and local (insertion and deletion) structural modification operators, that this problem can be almost eliminated even with trivial (stochastic hill-climbing) search methods, thus eliminating the above explanations. We argue, instead, that structural difficulty is a consequence of the large step size of the operators in standard genetic programming, which is itself a consequence of the fixed-arity property embodied in its representation. Representation and structural difficulty in genetic programming Nguyen Hoai RI Mckay D Essam doi:10.1109/TEVC.2006.871252 Evolutionary Computation, IEEE Transactions on, Vol. 10, No. 2. (2006), pp. 157-166. 2008-02-14T14:23:47-00:00 2006 Evolutionary Computation, IEEE Transactions on 10 2 157 166 evolution evolutionary-computation genetic-programming grammar modularity representation structures tag http://www.citeulike.org/user/mcphee/article/2373497 <i>Advances in Computation and Intelligence (2007), pp. 137-146.</i><br /><br />We investigate a developmental tree-adjoining grammar guided genetic programming system (DTAG3P + ), in which genetic operator application rates are adapted during evolution. We previously showed developmental evaluation could promote structured solutions and improve performance in symbolic regression problems. However testing on parity problems revealed an unanticipated problem, that good building blocks for early developmental stages might be lost in later stages of evolution. The adaptive variation rate in DTAG3P +  preserves good building blocks found in early search for later stages. It gives both good performance on small k-parity problems, and good scaling to large problems. Building on Success in Genetic Programming: Adaptive Variation and Developmental Evaluation Tuan-Hao Hoang Daryl Essam Bob Mckay Nguyen-Xuan Hoai doi:10.1007/978-3-540-74581-5_15 Advances in Computation and Intelligence (2007), pp. 137-146. 2008-02-14T11:51:11-00:00 2007 Advances in Computation and Intelligence 137 146 development evolutionary-computation genetic-programming grammar tag http://www.citeulike.org/user/mcphee/article/2373492 <i>Genetic Programming (2003), pp. 157-183.</i><br /><br />In this paper, we introduce a new grammar guided genetic programming system called tree-adjoining grammar guided genetic programming (TAG3P+), where tree-adjoining grammars (TAGs) are used as means to set language bias for genetic programming. We show that the capability of TAGs in handling context-sensitive information and categories can be useful to set a language bias that cannot be specified in grammar guided genetic programming. Moreover, we bias the genetic operators to preserve the language bias during the evolutionary process. The results pace the way towards a better understanding of the importance of bias in genetic programming. Tree Adjoining Grammars, Language Bias, and Genetic Programming Nguyen Hoai RI Mckay HA Abbass doi:10.1007/3-540-36599-0_31 Genetic Programming (2003), pp. 157-183. 2008-02-14T11:49:18-00:00 2003 Genetic Programming 157 183 evolution evolutionary-computation genetic-programming grammar tag http://www.citeulike.org/user/mcphee/article/305755 <i>(18 Aug 2005)</i><br /><br />Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url. We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge. The Structure of Collaborative Tagging Systems Scott Golder Bernardo Huberman (18 Aug 2005) 2005-08-27T17:06:09-00:00 2005 clustering collaborative_tagging delicious emergence folksonomies folksonomy information_organization no-tag self-organization social-networks socialtagging tag tagging tags