標(biāo)題: Titlebook: Genetic Programming; 11th European Confer Michael O’Neill,Leonardo Vanneschi,Ernesto Taranti Conference proceedings 2008 Springer-Verlag Be [打印本頁] 作者: Jackson 時(shí)間: 2025-3-21 19:16
書目名稱Genetic Programming影響因子(影響力)
書目名稱Genetic Programming影響因子(影響力)學(xué)科排名
書目名稱Genetic Programming網(wǎng)絡(luò)公開度
書目名稱Genetic Programming網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Genetic Programming被引頻次
書目名稱Genetic Programming被引頻次學(xué)科排名
書目名稱Genetic Programming年度引用
書目名稱Genetic Programming年度引用學(xué)科排名
書目名稱Genetic Programming讀者反饋
書目名稱Genetic Programming讀者反饋學(xué)科排名
作者: Crepitus 時(shí)間: 2025-3-21 21:52 作者: amnesia 時(shí)間: 2025-3-22 02:22 作者: 防銹 時(shí)間: 2025-3-22 07:24 作者: Crohns-disease 時(shí)間: 2025-3-22 10:54
Good News: Using News Feeds with Genetic Programming to Predict Stock Pricesal time from the Dow Jones network with news stories being classified as either Positive, Negative or Neutral in relation to a particular market or sector of interest..We show that with careful consideration to fitness function and data representation, GP can be used effectively to find non-linear s作者: DEI 時(shí)間: 2025-3-22 16:11 作者: DEI 時(shí)間: 2025-3-22 20:58
A SIMD Interpreter for Genetic Programming on?GPU?Graphics?Cards parallel consumer gaming graphics processing units. Using a Linux KDE computer equipped with an nVidia GeForce 8800 GTX graphics processing unit card the C++ SPMD interpretter evolves programs at Giga GP operations per second (895 million GPops). We use the RapidMind general processing on GPU (GPGP作者: 種類 時(shí)間: 2025-3-23 00:24 作者: Minikin 時(shí)間: 2025-3-23 01:27 作者: jeopardize 時(shí)間: 2025-3-23 09:21
Operator Equalisation and Bloat Free GPt limit, however, there may be program-length classes with a higher or lower average fitness than that achieved beyond the limit. Ideally, therefore, GP search should be limited to program lengths that are within the limit and that can achieve optimum fitness. This has the dual benefits of providing作者: BRIBE 時(shí)間: 2025-3-23 10:54 作者: Neutral-Spine 時(shí)間: 2025-3-23 16:59 作者: palpitate 時(shí)間: 2025-3-23 20:24
Crossover, Sampling, Bloat and the Harmful Effects of Size Limitsapping crossover when GP is applied to a flat fitness landscape. In that work, however, tree sizes are measured in terms of number of internal nodes. While the relationship between internal nodes and length is one-to-one for the case of .-ary trees, it is much more complex in the case of mixed ariti作者: 斥責(zé) 時(shí)間: 2025-3-23 23:55
The Performance of a Selection Architecture for Genetic Programmingchniques either try to identify and encapsulate useful code fragments as they evolve, or else they rely on intelligent prior deconstruction of the problem at hand. The alternative we propose is to base decomposition on a partitioning of the input test cases into subsets or ranges. To effect this, th作者: archaeology 時(shí)間: 2025-3-24 03:55
A Comparison of Cartesian Genetic Programming and Linear Genetic Programming formal algorithm for constructing a directed acyclic graph (DAG) from a classical LGP instruction sequence has been established. Given graph-based LGP and traditional CGP, this paper investigates the similarities and differences between the two implementations, and establishes that the significant 作者: BOLUS 時(shí)間: 2025-3-24 07:05
Evolvability Via Modularity-Induced Mutational Focussingerstood concept at present: it is unclear precisely how the genotype-phenotype map aligns random genotypic mutation with favourable phenotypic variation. By static analysis of the distribution of the genotypic representation of functionality, an emergent bias in the representation of the adapted and作者: Concerto 時(shí)間: 2025-3-24 11:47 作者: 刺耳的聲音 時(shí)間: 2025-3-24 15:42 作者: 亞麻制品 時(shí)間: 2025-3-24 21:27 作者: DEMUR 時(shí)間: 2025-3-24 23:41 作者: Constant 時(shí)間: 2025-3-25 03:28
Practical Model of Genetic Programming’s Performance on Rational Symbolic Regression ProblemsMany theoretical studies on GP are criticized for not being applicable to the real world. Here we present a practical model for the performance of a standard GP system in real problems. The model gives accurate predictions and has a variety of applications, including the assessment of the similarities and differences of different GP systems.作者: OREX 時(shí)間: 2025-3-25 10:06
978-3-540-78670-2Springer-Verlag Berlin Heidelberg 2008作者: 夜晚 時(shí)間: 2025-3-25 14:34
Genetic Programming978-3-540-78671-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Abrade 時(shí)間: 2025-3-25 18:40 作者: 徹底檢查 時(shí)間: 2025-3-25 21:35
Gerhard Lippe,J?rn Esemann,Thomas T?nzerthe Ant Wars contestants was to evolve a controller for a virtual ant that collects food in a square toroidal grid environment in the presence of a competing ant. BrilliAnt, submitted to the contest by our team, has been evolved through competitive one-population coevolution using genetic programmin作者: 附錄 時(shí)間: 2025-3-26 00:36
https://doi.org/10.1007/978-3-658-26836-7al evolution. However, few coevolutionary experiments have been reported. Here we describe the results of our experiments on the evolution of physical combat among virtual creatures: essentially, we evolve creatures that trade blows with each other. While several authors have involved highly abstrac作者: poliosis 時(shí)間: 2025-3-26 05:53
Das Wohnerlebnis in Deutschlanddegraded due to various network related problems. In this paper we present a model for speech quality estimation that is a function of various time and frequency domain features of human speech. We have employed a hybrid optimization approach, by using Genetic Programming (GP) to find a suitable str作者: 詞匯記憶方法 時(shí)間: 2025-3-26 10:33 作者: 容易做 時(shí)間: 2025-3-26 13:30 作者: SEEK 時(shí)間: 2025-3-26 17:27
Regierungserkl?rung vom 18. Oktober 1963 parallel consumer gaming graphics processing units. Using a Linux KDE computer equipped with an nVidia GeForce 8800 GTX graphics processing unit card the C++ SPMD interpretter evolves programs at Giga GP operations per second (895 million GPops). We use the RapidMind general processing on GPU (GPGP作者: 招惹 時(shí)間: 2025-3-26 22:03
Wettbewerbsimplementierung im Sozialwesen,to break the initial problem down into smaller sub-tasks. In particular, a decomposition approach has been described that is based on partitioning of the circuit test vectors, but it has its limitations. In an effort to address this, we have combined the partitioning method with an incrementally evo作者: 招人嫉妒 時(shí)間: 2025-3-27 02:05 作者: WAX 時(shí)間: 2025-3-27 08:49
Perspektiven von Journalismus auf t limit, however, there may be program-length classes with a higher or lower average fitness than that achieved beyond the limit. Ideally, therefore, GP search should be limited to program lengths that are within the limit and that can achieve optimum fitness. This has the dual benefits of providing作者: 可轉(zhuǎn)變 時(shí)間: 2025-3-27 12:14 作者: 共同時(shí)代 時(shí)間: 2025-3-27 16:05 作者: fiscal 時(shí)間: 2025-3-27 19:27 作者: 去世 時(shí)間: 2025-3-27 22:19 作者: 易怒 時(shí)間: 2025-3-28 02:51
Borderline-Pers?nlichkeitsst?rung formal algorithm for constructing a directed acyclic graph (DAG) from a classical LGP instruction sequence has been established. Given graph-based LGP and traditional CGP, this paper investigates the similarities and differences between the two implementations, and establishes that the significant 作者: amyloid 時(shí)間: 2025-3-28 08:43 作者: Synovial-Fluid 時(shí)間: 2025-3-28 14:08
https://doi.org/10.1007/978-3-322-98768-6probability distribution of triplets of instructions (or 3-grams) at the same time as it is learning and sampling a program length distribution. We have tested N-gram GP on symbolic regressions problems where the target function is a polynomial of up to degree 12 and lawn-mower problems with lawn si作者: 微不足道 時(shí)間: 2025-3-28 16:22
Karl Leberecht Immermann ?Münchhausen?with the environment; to this end, a function of the state of the agent has to be learned. It is often the case that states are better characterized by a set of features. However, finding a “good” set of features is generally a tedious task which requires a good domain knowledge. In this paper, we p作者: 健忘癥 時(shí)間: 2025-3-28 20:14 作者: elucidate 時(shí)間: 2025-3-29 00:15 作者: 氣候 時(shí)間: 2025-3-29 06:31 作者: 減弱不好 時(shí)間: 2025-3-29 09:25 作者: intolerance 時(shí)間: 2025-3-29 13:49 作者: Kaleidoscope 時(shí)間: 2025-3-29 19:20 作者: 整潔漂亮 時(shí)間: 2025-3-29 20:45 作者: Accede 時(shí)間: 2025-3-30 01:06 作者: 雇傭兵 時(shí)間: 2025-3-30 05:24 作者: 贊美者 時(shí)間: 2025-3-30 11:00 作者: excursion 時(shí)間: 2025-3-30 14:02 作者: exhibit 時(shí)間: 2025-3-30 20:14
A Comparison of Cartesian Genetic Programming and Linear Genetic Programmingdifference between them is each algorithm’s means of restricting inter-connectivity of nodes. The work then goes on to compare the performance of two representations each (with varied connectivity) of LGP and CGP to a directed cyclic graph (DCG) GP with no connectivity restrictions on a medical classification and regression benchmark.作者: 座右銘 時(shí)間: 2025-3-30 22:34
https://doi.org/10.1007/978-3-658-26836-7w much each colliding limb contributed to the occurrence and depth of the collision. Our system successfully evolves a wide range of morphologies and fighting behaviours, which we describe visually and verbally. As with our previous efforts, our source code is publicly available.作者: 炸壞 時(shí)間: 2025-3-31 02:05
https://doi.org/10.1007/978-3-322-98899-7er before the data is finally stored as an image file. We show how genetic programming may be used to obtain the sensor response functions using a single image from a calibration target as input together with the reflectance data of this calibration target.作者: bizarre 時(shí)間: 2025-3-31 06:41 作者: 險(xiǎn)代理人 時(shí)間: 2025-3-31 13:04
A Genetic Programming Approach to Deriving the Spectral Sensitivity of an Optical Systemer before the data is finally stored as an image file. We show how genetic programming may be used to obtain the sensor response functions using a single image from a calibration target as input together with the reflectance data of this calibration target.作者: plasma-cells 時(shí)間: 2025-3-31 15:07 作者: 粘連 時(shí)間: 2025-3-31 19:05 作者: BLAZE 時(shí)間: 2025-4-1 01:29
Regierungserkl?rung vom 18. Oktober 1963 the C++ SPMD interpretter evolves programs at Giga GP operations per second (895 million GPops). We use the RapidMind general processing on GPU (GPGPU) framework to evaluate an entire population of a quarter of a million individual programs on a non-trivial problem in 4 seconds. An efficient reverse polish notation (RPN) tree based GP is given.作者: Abominate 時(shí)間: 2025-4-1 02:56 作者: Rankle 時(shí)間: 2025-4-1 06:25 作者: ensemble 時(shí)間: 2025-4-1 13:18
https://doi.org/10.1007/978-3-531-92447-2on. By static analysis of the distribution of the genotypic representation of functionality, an emergent bias in the representation of the adapted and maladapted is shown. This bias is facilitated by a form of reuse modularity, and it serves to direct phenotypic variation to where there is selective opportunity.
