著者

小野 功龍

出版者

相愛女子大学相愛女子短期大学

雑誌

相愛女子大学相愛女子短期大学研究論集

巻号頁・発行日

vol.12-13, no.2, pp.144-131, 1966-02

著者

中村 覚 佐久間 淳 小林 重信 小野 功

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第22回全国大会(2008)

巻号頁・発行日

pp.83, 2008 (Released:2009-07-31)

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本論文では,クォートドリブン市場におけるマーケットメーカー(MM)の戦略獲得問題を,MMの利益および約定率の観点から多目的最適化問題として定式化し,多目的遺伝的アルゴリズムにより戦略の最適化を行う手法を提案する.

著者

佐藤 浩 小野 功 小林 重信

出版者

社団法人人工知能学会

雑誌

人工知能学会誌 (ISSN:09128085)

巻号頁・発行日

vol.12, no.5, pp.734-744, 1997-09-01

被引用文献数

211

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When Genetic Algorithms (GAs) are applied to optimization problems, characteristic preserving in designing coding/crossover and diversity maintaining in designing generation alternation are important. Generation alternation models are independent of problems, while coding/crossover depends on problems. We discuss generation alternation models in this paper. Simple GA is one of the well-known generation alternation models, however it has two problems. One is early convergence in the first stage of search and the other is evolutionary stagnation in the last stage of it. Many improvements and new models have been presented to overcome the above problems. In this paper, we propose a new generation alternation model called minimal generation gap (MGG) which has all advantages of conventional models. As generation alternation models use only information of fitness, alternation of generations can be regarded as a transformation of fitness distributions. We propose a new method of assessing generation alternation models. We measure the ability of avoiding the early convergence and suppressing the evolutionary stagnation by the dynamics of the best value and variance of fitness distributions. From the results of some experiments, we found that MGG is the most desirable model which can avoid the early convergence and suppress the evolutionary stagnation. We also show the efficiency of MGG by applying it to benchmarks in different two domains: function optimization and traveling salesman problems. In the both domains, MGG showed higher performance than the other conventional models especially under small population size.

著者

佐藤 浩 小野 功 小林 重信

出版者

一般社団法人 人工知能学会

雑誌

人工知能 (ISSN:21882266)

巻号頁・発行日

vol.12, no.5, pp.734-744, 1997-09-01 (Released:2020-09-29)

被引用文献数

5

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When Genetic Algorithms (GAs) are applied to optimization problems, characteristic preserving in designing coding/crossover and diversity maintaining in designing generation alternation are important. Generation alternation models are independent of problems, while coding/crossover depends on problems. We discuss generation alternation models in this paper. Simple GA is one of the well-known generation alternation models, however it has two problems. One is early convergence in the first stage of search and the other is evolutionary stagnation in the last stage of it. Many improvements and new models have been presented to overcome the above problems. In this paper, we propose a new generation alternation model called minimal generation gap (MGG) which has all advantages of conventional models. As generation alternation models use only information of fitness, alternation of generations can be regarded as a transformation of fitness distributions. We propose a new method of assessing generation alternation models. We measure the ability of avoiding the early convergence and suppressing the evolutionary stagnation by the dynamics of the best value and variance of fitness distributions. From the results of some experiments, we found that MGG is the most desirable model which can avoid the early convergence and suppress the evolutionary stagnation. We also show the efficiency of MGG by applying it to benchmarks in different two domains: function optimization and traveling salesman problems. In the both domains, MGG showed higher performance than the other conventional models especially under small population size.

著者

小野 功一郎

出版者

桃山学院教育大学

雑誌

紀要「エレノア」 = Eleanor

巻号頁・発行日

vol.1, pp.83-95, 2019-04-01

著者

益富 和之 永田 裕一 小野 功

出版者

進化計算学会

雑誌

進化計算学会論文誌 (ISSN:21857385)

巻号頁・発行日

vol.6, no.1, pp.1-12, 2015 (Released:2015-04-28)

参考文献数

28

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This paper proposes a novel evolution strategy for noisy function optimization. We consider minimization of the expectation of a continuous domain function with stochastic parameters. The proposed method is an extended variant of distance-weighted exponential evolution strategy (DX-NES), which is a state-of-the-art algorithm for deterministic function optimization. We name it DX-NES for uncertain environments (DX-NES-UE). DX-NES-UE estimates the objective function by a quadratic surrogate function. In order to make a balance between speed and accuracy, DX-NES-UE uses surrogate function values when the noise is strong; otherwise it uses observed objective function values. We conduct numerical experiments on 20-dimensional benchmark problems to compare the performance of DX-NES-UE and that of uncertainty handling covariance matrix adaptation evolution strategy (UH-CMA-ES). UH-CMA-ES is one of the most promising methods for noisy function optimization. Benchmark problems include a multimodal function, ill-scaled functions and a non-C2 function with additive noise and decision variable perturbation (sometime called actuator noise). The experiments show that DX-NES-UE requires about 1/100 times as many observations as UH-CMA-ES does on well-scaled functions. The performance difference is greater on ill-scaled functions.

著者

神谷 昭基 小野 功 小林 重信

出版者

一般社団法人 電気学会

雑誌

電気学会論文誌C(電子・情報・システム部門誌) (ISSN:03854221)

巻号頁・発行日

vol.117, no.7, pp.829-836, 1997-06-20 (Released:2008-12-19)

参考文献数

13

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Start-up scheduling is aimed at minimizing the start-up time while limiting turbine rotor stresses to an acceptable level. This scheduling problem has a wide search space. In order to improve the search efficiency and robustness and to establish an adaptive search model, we propose to integrate evolutionary computation, based on Genetic Algorithms (GA), with reinforcement learning. The strategies with our proposal include: multi-boundary-based enforcement operator and multi-elitist plan. By setting a second boundary, located right outside the existing boundary containing those feasible schedules, we extend our proposed enforcement operator and the conventional elitist plan into the multi-boundary-based enforcement operator and multi-elitist plan. These two strategies work together to focus the search along the boundary, around which the optimal schedule is supposed to exist, so as to increase the search efficiency as well as its robustness. During a search process, GA guides the reinforcement learning to concentrate its learning on those promising areas instead of the entire space. In return, reinforcement learning can generate a good schedule, in the earlier stage of the search process. We obtain encouraging test results. In this paper, we propose the GA-based search model with these strategies and discuss the test results.

著者

小野 功 水口 尚亮 中島 直敏 小野 典彦 中田 秀基 松岡 聡 関口 智嗣 楯 真一

出版者

一般社団法人情報処理学会

雑誌

情報処理学会論文誌コンピューティングシステム(ACS) (ISSN:18827829)

巻号頁・発行日

vol.46, no.12, pp.396-406, 2005-08-15

被引用文献数

3

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本論文では,Ono らが提案したNMR 蛋白質立体構造決定のための遺伝アルゴリズム(GA)を,複数のWAN 上のPC クラスタ群から構成されるグリッド上で並列化したシステムを提案し,提案システムの性能評価を行った結果を報告する.提案システムは,マスタ,サブマスタ,ワーカから構成される階層的なマスタ・ワーカ方式を用いて並列化されている.マスタと各PC クラスタ間の通信はセキュアなGridRPC ミドルウェアNinf-G を用いて,また,PC クラスタ内の通信は高速なGridRPCミドルウェアNinf-1 を用いて実現されている.さらに,提案システムでは,Ninf-G によるインターネット上の通信遅延を隠蔽するため,スライド転送手法を導入している.5 サイト/1 196CPU から構成されるグリッドテストベッドで,78 残基からなる蛋白質の立体構造決定問題を用いて,提案システムの性能評価を行った結果,高い並列化効率を示すことが確認された.In this paper, we parallelize the genetic algorithm (GA) for NMR protein three-dimensional structure determination, which has been proposed by Ono et al., on a grid that consists of multiple PC clusters on the WAN and report some results on the performance evaluation of the proposed system. The proposed system is parallelized with the hierarchical master-worker paradigm and consists of a master, submasters and workers. The communication between the master and each PC cluster is realized with Ninf-G, which is a secure GridRPC middleware, and that in each PC cluster is implemented by using Ninf-1, which is a fast GridRPC middleware. In the proposed system, we employ the slide transfer technique in order to hide the latency of communication on the Internet by using Ninf-G. The experimental results on the grid testbed consisting of 5 sites/1,196 CPUs showed that the proposed system effectively utilized computing resources on the grid testbed when it was applied to a problem of determining the three-dimensional structure of a 78-residue protein.

著者

小野 功一郎

出版者

大和大学

雑誌

大和大学研究紀要. 教育学部編 = Journal of Yamato University. 大和大学研究紀要教育学部編集委員会 編 (ISSN:24325600)

巻号頁・発行日

vol.4, pp.91-100, 2018-03

著者

小野 功一郎

出版者

日本デジタル教科書学会

雑誌

日本デジタル教科書学会発表予稿集 日本デジタル教科書学会第7回年次大会 (ISSN:24326127)

巻号頁・発行日

pp.89-90, 2018 (Released:2018-10-03)

参考文献数

2

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本研究ではSociety5.0を見据えドローンを使用し、遊び感覚でプログラミングに触れることで子供がプログラミングの可能性や面白さを発見ができるようなプログラミング教育の手法を提言する。

著者

小野 功一郎

出版者

日本デジタル教科書学会

雑誌

日本デジタル教科書学会発表予稿集 日本デジタル教科書学会第6回年次大会 (ISSN:24326127)

巻号頁・発行日

pp.31-32, 2017 (Released:2017-12-07)

参考文献数

1

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平成32年度(2020年度)から実施される小学校新学習指導要領では、「プログラミングを体験しながら論理的思考力を身に付ける」と明記され、プログラミング教育が必修化となる。 児童にわかりやすく教えるにはどうすれば良いのか?どのようなプログラミングシステムがあるのか? Scratch・MOONBlock・プログラミン・VISCUIT・Google Blocklyというプログラミングシステムを実際にプログラミンしてみながら比較研究し、図工を例として授業をおこなう教育内容・教育教材を提案する。

著者

上村 健人 木下 峻一 永田 裕一 小林 重信 小野 功

出版者

進化計算学会

雑誌

進化計算学会論文誌 (ISSN:21857385)

巻号頁・発行日

vol.4, no.1, pp.1-12, 2013 (Released:2013-03-02)

参考文献数

18

被引用文献数

1

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This paper proposes a new framework of real-coded genetic algorithms (RCGAs) for the multi-funnel function optimization. The RCGA is one of the most powerful function optimization methods. Most conventional RCGAs work effectively on the single-funnel function that consists of a single big-valley. However, it is reported that they show poor performance or, sometimes, fail to find the optimum on the multi-funnel function that consists of multiple big-valleys. In order to remedy this deterioration, Innately Split Model (ISM) has been proposed as a framework of RCGAs. ISM initializes an RCGA in a small region and repeats a search with the RCGA as changing the position of the region randomly. ISM outperforms conventional RCGAs on the multi-funnel functions. However, ISM has two problems in terms of the search efficiency and the difficulty of setting parameters. Our proposed method, Big-valley Explorer (BE), is a framework of RCGAs like ISM and it has two novel mechanisms to overcome these problems, the big-valley estimation mechanism and the adaptive initialization mechanism. Once the RCGA finishes a search, the big-valley estimation mechanism estimates a big-valley that the RCGA already explored and removes the region from the search space to prevent the RCGA from searching the same big-valley many times. After that, the adaptive initialization mechanism initializes the RCGA in a wide unexplored region adaptively to find unexplored big-valleys. We evaluate BE through some numerical experiments with both single-funnel and multi-funnel benchmark functions.

著者

福島 信純 永田 裕一 小林 重信 小野 功

出版者

進化計算学会

雑誌

進化計算学会論文誌 (ISSN:21857385)

巻号頁・発行日

vol.4, no.2, pp.57-73, 2013 (Released:2013-09-11)

参考文献数

19

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The natural evolution strategies (NESs) is a family of iterative methods for black-box function optimization. Instead of directly minimizing an objective function, NESs minimizes the expectation of the objective function value over an arbitrary parametric probability distribution. In each iteration, NESs updates parameters of the distribution by using an estimated natural gradient of the expectation of the objective function value. Exponential NES (xNES) is an effective method of NESs that uses the multivariate normal distribution as the probability distribution. Since the shape of a normal distribution can take the form of a rotated ellipse in the solution space, xNES shows relatively good performance for ill-conditioned and non-separable objective functions. However, we believe that xNES has two problems that cause performance degradation. The first problem is that the spread of normal distribution tends to shrink excessively even if the distribution does not cover a (local) optimal point. This will cause premature convergence. The second problem is that the learning rates for the parameters of distribution are not appropriate. The learning rates depend only on the dimension of objective function although they should be designed depending on all the factors that influence the precision of natural gradient estimation. Moreover, they are set to small values for preventing the premature convergence and these results in too slow convergence speed even if the distribution covers the optimal point. In order to remedy the problems of xNES, we propose a new method of NESs named the distance-weighted exponential natural evolution strategy (DX-NES). On several benchmark functions, we confirmed that DX-NES outperforms xNES and that DX-NES shows better performance than CMA-ES on the almost all functions.

著者

小野 功喜 高須 昌子 古川 英光

出版者

一般社団法人日本物理学会

雑誌

日本物理学会講演概要集 (ISSN:13428349)

巻号頁・発行日

vol.60, no.2, 2005-08-19

著者

太田 憲良 高須 昌子 小野 功喜 古川 英光

出版者

一般社団法人日本物理学会

雑誌

日本物理学会講演概要集 (ISSN:13428349)

巻号頁・発行日

vol.63, no.1, 2008-02-29

著者

合田 憲人 大澤 清 大角 知孝 笠井 武史 小野 功 實本 英之 松岡 聡 斎藤 秀雄 遠藤 敏夫 横山 大作 田浦 健次朗 近山 隆 田中 良夫 下坂 久司 梶原広輝 廣安 知之 藤澤克樹

出版者

一般社団法人情報処理学会

雑誌

情報処理学会研究報告ハイパフォーマンスコンピューティング(HPC) (ISSN:09196072)

巻号頁・発行日

vol.2006, no.87, pp.49-54, 2006-07-31

被引用文献数

3

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本稿では,2005年12月から2006年5月にかけて実施されたGrid Challenge in SACSIS2006において使用されたグリッド実験環境の構築・運用事例を報告する.Grid Challengeは,大学,研究所が提供する複数の計算資源からなるグリッド実験環境上で,参加者がプログラミング技術を競う大会であり,今大会では1200CPU超の計算資源からなるグリッド実験環境が運用された.本稿では,実験環境ハードウェアおよびソフトウェアの仕様を紹介するとともに,ユーザ管理,ジョブ管理,障害対応といった運用事例についても報告する.This paper presents a case study to operate the Grid testbed for the Grid Challenge in SACSIS2006. The Grid Challenge is a programming competition on a Grid testbed, which is organized by multiple computing resources installed in universities and laboratories. In the last competition, the Grid testbed with more than 1200 CPUs was operated. The paper shows hardware/software specifications of the Grid testbed, and reports experience of the operation, which includes accounting, job management, and troubleshooting.

著者

小野 功 小林 重信

出版者

社団法人人工知能学会

雑誌

人工知能学会誌 (ISSN:09128085)

巻号頁・発行日

vol.13, no.5, pp.780-790, 1998-09-01

被引用文献数

13

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In this paper, we propose a new genetic algorithm(GA) for job-shop scheduling problems(JSPs), considering dependencies among machines. We regard the crossover as a main search operator. Crossovers should preserve characteristics between parents and their children in order for GAs to perform well. Characteristics are elements that constitute a solution and determine the fitness of the solution. Chracteristics also should be highly independent of each other. A characteristic has to be found for each problem domain since it depends on a particular problem domain. We basically regard the processing order of jobs as a characteristic for JSPs. We consider job-based order inheritance and position-based order inheritance for ways of inheritance of the processing order by crossovers, and propose two new crossovers; the Inter-machine Job-based Order Crossover(Inter-machine JOX) and the Inter-machine Position-based Order Crossover(Inter-machine POX). By applying them to the benchmark problems of FT10×10 and FT20×5, we demonstrate that the Inter-machine JOX shows better performance than the Inter-machine POX and an existing crossover, the SXX[Kobayashi 95]. The Inter-machine JOX preserves both the processing order of jobs and the technological ordering which causes dependencies among machines. We also propose a new mutation named the Inter-machine Job-based Shift Change for introducing a diversity of population. We confirm its effectiveness by applying it with the Inter-machine JOX to FT10×10 and FT20×5.