研究者詳細 - 大西　圭

論文 - 大西　圭

分割表示 >> ／全件表示57 件中 1 - 57 件目

Noncooperative Population-Based Search Relying on Spatial and/or Temporal Scale-Free Behaviors of Individuals 査読有り国際誌

Ohnishi K.

Journal of Robotics and Mechatronics ( 富士技術出版株式会社 ) 36 ( 3 ) 618 - 627 2024年06月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

Although individuals of species engaging in cooperative foraging behaviors are often modeled as swarm intelligence optimization algorithms, there are also several species whose individuals take noncooperative foraging behaviors. Some such species exhibit common behaviors, which we call scale-free behaviors in this study. A type of scale-free behavior is spatial scale-free behavior, in which the moving distance of an individual from the present food source follows a power-law distribution. Second, the staying duration of an individual at the current food source follows a power-law distribution, and this behavior is called temporal scale-free behavior. We propose two types of noncooperative population-based search methods, based on the two types of scale-free behaviors. We also conducted simulations to compare the two methods, assuming static and dynamic environments in which the position of the food source did not change and changed, respectively. The simulation results showed that temporal scale-free behavior is suitable for specific problems in which individuals around the global optimum can be eliminated probabilistically, and spatial scale-free behavior is suitable for problems in which such elimination never occurs. In other words, the two types of scale-free behaviors are complementary. Next, we first assume problems for which we cannot know if the probabilistic elimination of individuals occurs in advance, and then propose a search method that selects an appropriate type of scale-free behavior for individuals during the search. The simulation results showed that this method demonstrates a good search performance, on average, for such problems.

DOI： 10.20965/jrm.2024.p0618

Scopus

CiNii Research

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Probabilistic Model Building Evolutionary Algorithm Using the Same Type and Size of Model for Any Binary Optimization Problems 査読有り国際誌

Kishimoto A., Ohnishi K.

2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024 2024年01月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We propose a new probabilistic model building evolutionary algorithm that uses the same type and size of probabilistic model for any binary optimization problems. The proposed method represents a population as a binary matrix for any binary optimization problems and solves a given problem by transforming the population in the form of matrix to better one with 512 production rules of cellular automaton. Concretely, the proposed method builds a probabilistic model for generating new solution candidates while applying the 512 production rules to the matrix representing the population. The probabilistic model consists of the 512 inverse production rules and their application probabilities. The strong point of the proposed method is to be able to transform any binary optimization problems to the same size of 512-bit production rule optimization problem. Since the proposed method treats any binary optimization problems in a unified manner, we can easily explore a robust method for various binary optimization problems as the proposed method with particular configurations. As the first evaluation of the proposed method, we apply the proposed method to the same kind but different sizes of problems. The results show that depending strongly on the bit patterns of the global optima, the proposed method with the same configurations realizes a good scalability of the number of function evaluations required for obtaining near optimum to the problem size growth.

DOI： 10.1109/SCISISIS61014.2024.10760174

Scopus

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Real-time Support for Solution Search in Human-based Evolutionary Computation 査読有り国際誌

Utsumi T., Muta H., Tsung C.K., Ohnishi K.

2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024 2024年01月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We propose a method to extract important words common to good solution candidates in human-based evolutionary computation, like building blocks in genetic algorithms, and present them to the participants in a realtime manner. We also propose a method to obtain and present words similar to the important ones. Furthermore, we propose a method to measure the similarity between participants using the important words for each participant and present it to the participants. All of the proposed methods help participants solve problems by reducing the cognitive load of finding key words and persons. We implement those methods into a human-based evolutionary computation system and evaluate the proposed methods through human subject experiments using the system. The experimental results show that although the evaluation result to the outputs from the system incorporating the methods by a third party is not so good, the system is shown to be useful for participants to create solutions.

DOI： 10.1109/SCISISIS61014.2024.10759881

Kyutacar

Scopus

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人間ベース進化計算とChatGPTの実験による比較

大西圭, 釘宮由成, 吉川大弘

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 40 ( 0 ) 558 - 563 2024年01月

群知能最適化手法間の類似度測定方法の提案

大西圭, 村上楓

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 40 ( 0 ) 578 - 583 2024年01月

Comparison of Quality-based and Quantity-based Real-time Rankings of Participants in Human-based Evolutionary Computation Systems 査読有り国際誌

Hiroki Muta, Kei Ohnishi

The 20th World Congress of the International Fuzzy Systems Association (IFSA 2023) 146 - 152 2023年08月

協調戦略を持つ個体の集団による生存ゲームとしての進化計算

大西圭

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 39 ( 0 ) 672 - 677 2023年01月

ビルディングブロック提示機能を実装した人間ベース進化計算システム

牟田大輝, 大西圭

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 39 ( 0 ) 678 - 683 2023年01月

Swarm Intelligence Numerical Optimization Algorithm Representing Individuals as Dynamic Graphs in the Euclidean Search Space 査読有り国際誌

Hayashi K., Ohnishi K.

2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 1201 - 1207 2023年01月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We propose a new swarm intelligence numerical optimization algorithm that represents individuals as dynamic graphs in the Euclidean search space. We call it Graph Building Optimization Algorithm or GBO. The unique point of GBO is that an individual is represented by a dynamic graph whose nodes have coordinates (search points) in the Euclidean search space. Due to this unique point, we can draw a GBO's search process as a generation-transition of a feature of a graph. It is expected that we can obtain better understandings on a given problem by comparing the generation-transition for the given problem to the baseline for the simplest unimodal problem. We assume the maximum node degree in the best individual as the feature and the generation-transition of the feature for F1 in the CEC'13 test problems as the baseline. We demonstrate that we can guess the characteristics of other 27 problems in the CEC'13 test problems by comparing their generation-transitions to the baseline. In addition, we evaluate GBO using the same problems and show that GBO is capable of finding good solutions for various problems.

DOI： 10.1109/SSCI52147.2023.10371876

Scopus

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Framework of Systems for Creating Intelligent Behaviors of Imaginary Creatures for Humans 査読有り国際誌

Ohnishi K., Kumano Y.

2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 1195 - 1200 2023年01月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

The paper proposes a framework of systems for creating intelligent behaviors of imaginary creatures for humans, which is built upon a framework of swarm intelligence optimization algorithms. The paper assumes and models an imaginary slime mold, which is an amoeboid unicellular creature, as an imaginary creature in the framework concretely. In addition, the paper conducts basic evaluations of the framework. Various swarm intelligence optimization algorithms have been proposed so far, but there is a common feature among them. That is that a set of search points in a search space, which are called individuals, move around in the space according to algorithm specific rules using fitness values of the individuals, and the differences among algorithms are in algorithm specific rules. Therefore, under the use of one swarm intelligence optimization algorithm, that is, one particular set of rules, if a fitness function is varied, behaviors of individuals are also varied. Based on this fact, the proposed framework optimizes a parametric fitness function for individuals to behave intelligently for a human. In the basic evaluation of the concrete system, a fitness function of computer program which returns a fitness value calculated with a distribution of individuals is used instead of a human, and it is demonstrated that optimization of a parametric fitness function indeed yields desired behaviors of individuals.

DOI： 10.1109/SSCI52147.2023.10371904

Scopus

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Experiment to Investigate Awareness of Tastes for Users in Interactive Evolutionary Computation 査読有り国際誌

Obata R., Ohnishi K., Fukumoto M., Ohsaki M.

2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022 2022年11月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Interactive evolutionary computation (IEC) is one type of evolutionary computation which includes a human user as an evaluation system. Unlike a computer program in standard EC, an IEC user is expected to be aware of his/her tastes more clearly with iteration of evaluations. However, there has not been any research that tries to confirm it so far. If it is confirmed, IEC is desired to design based on that fact. In the paper we first propose an experimental way to investigate it and then conduct an experiment following the proposed way. In addition, we try to extract features of solutions which correspond to the awareness well. The results show that most subjects can be more aware of their tastes with iteration and the extracted features correspond to the awareness well.

DOI： 10.1109/SCISISIS55246.2022.10002067

Scopus

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Evolutionary Computation System Solving Group Decision Making Multiobjective Problems for Human Groups 査読有り国際誌

Hironao Sakamoto, Kotaro Nakamoto, and Kei Ohnishi

Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII) 26 ( 2 ) 196 - 205 2022年03月

Test Problem in Which Bits Used for Fitness Calculation Depend on Bit Pattern" 査読有り国際誌

Kei Ohnishi, Daiki Koga, and Tian-Li Yu

IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021) 2021年12月

Non-generational Geometric Semantic Genetic Programming 査読有り国際誌

Daiki Koga and Kei Ohnishi

IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021) 2021年12月

NNR-GL: A Measure to Detect Co-Nonlinearity Based on Neural Network Regression Regularized by Group Lasso 査読有り国際誌

Miho Ohsaki, Naoya Kishimoto, Hayato Sasaki, Ryoji Ikeura, Shigeru Katagiri, Kei Ohnishi, Yakub Sebastian, and Patrick Then

IEEE Access 9 132033 - 132052 2021年09月

Evaluation of the Neural-network-based Method to Discover Sets and Representatives of Nonlinearly Dependent Variables 査読有り

Ohsaki M., Sasaki H., Kishimoto N., Katagiri S., Ohnishi K., Sebastian Y., Then P.

2021 5th IEEE International Conference on Cybernetics, CYBCONF 2021 101 - 106 2021年06月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

It is desired in a variety of fields to identify which variables are dependent, and variable dependence measures have been studied. The majority of such measures detect a linear or a certain range of nonlinear dependence between paired variables. To go beyond them, a method based on Neural Network Regression, Group Lasso, and Information Aggregation has been proposed in our past study. It can detect a wide range of nonlinear dependences among multi variables and discover the sets and representatives of the detected dependences. Its fundamental effectiveness has already been examined using synthesized artificial datasets containing a single dependence. For further evaluation in the present study, we conducted an experiment using those containing multi dependences. The proposed method succeeded in discovering the sets and representatives, and its performance was robust to data size and noise rate. The experimental results suggested that the proposed method works well for difficult tasks to handle multi dependences.

DOI： 10.1109/CYBCONF51991.2021.9464151

Scopus

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Acquiring Consensus Solutions by Multi-human-agent-based Evolutionary Computation 査読有り国際誌

Sakamoto H., Nakamoto K., Ohnishi K.

2021 5th IEEE International Conference on Cybernetics, CYBCONF 2021 12 - 18 2021年06月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

The paper proposes a system to acquire consensus solutions among people to a multiobjective problem which does not require direct communication among the people. It relies on multi-human-agent-based evolutionary computation (Mhab-EC) with a mechanism for making solutions of agents converged. In the system, people prepare their own agents who can be tuned by themselves, and then submit their agents to a simulation of Mhab-EC and acquire a convergence solution from the simulation. Then, examining the simulation result, they tune their agents again to be closer to their desired solutions and submit the agents to the simulation and obtain a convergence solution. The mechanism repeats this procedure pre-determined times and outputs a convergence solution of the final simulation as the consensus solution. In basic evaluation of the system, we focus on if the system can make solution converged and show that it can indeed do it.

DOI： 10.1109/CYBCONF51991.2021.9464147

Scopus

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Genetic algorithms using neural network regression and group lasso for dynamic selection of crossover operators 査読有り

Kato M., Ohsaki M., Ohnishi K.

2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020 2020年12月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We propose real-coded genetic algorithms that utilize a method for detecting dependency relationships between variables. The method consists of neural network regression and group lasso. The proposed genetic algorithms select an appropriate crossover operator based on dependency information between variables, which are obtained from past solution candidates. Simulation results using the CEC'13 benchmark functions show that the proposed algorithms outperform conventional real-coded genetic algorithms.

DOI： 10.1109/SCISISIS50064.2020.9322697

Scopus

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An evolutionary algorithm inspired by evolution of birdsong grammars to quickly obtain practical solutions to large-scaled problems 査読有り

Tabata N., Ohnishi K.

2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020 2020年12月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We propose an evolutionary algorithm inspired by evolution of birdsong grammars. The proposed algorithm is designed to quickly obtain practical solutions to large-scaled problems. The main mechanism for obtaining practical solutions quickly is to represent solution candidates in a compact way using grammars, that is to say, to make the search space smaller than the original one using grammars. Also, we apply the algorithm to a large-scaled OneMax problem and its variants. The simulation results show that the algorithm tends to quickly produce solution candidates with simple bit patterns and with not so bad fitness values for large-scaled problems as a bit pattern of the global optimum becomes more random. That can be considered as that practical solutions to large-scaled problems are obtained quickly. It is also shown that when the problem size is smaller, the algorithm tends to produce a precise bit pattern of the global optimum.

DOI： 10.1109/SCISISIS50064.2020.9322703

Scopus

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An empirical investigation on evolutionary algorithm evolving developmental timings 査読有り

Ohnishi K., Hamano K., Koeppen M.

Electronics (Switzerland) 9 ( 11 ) 1 - 27 2020年11月

担当区分：責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

Recently, evolutionary algorithms that can efficiently solve decomposable binary optimization problems have been developed. They are so-called model-based evolutionary algorithms, which build a model for generating solution candidates by applying a machine learning technique to a population. Their central procedure is linkage detection that reveals a problem structure, that is, how the entire problem consists of sub-problems. However, the model-based evolutionary algorithms have been shown to be ineffective for problems that do not have relevant structures or those whose structures are hard to identify. Therefore, evolutionary algorithms that can solve both types of problems quickly, reliably, and accurately are required. The objective of the paper is to investigate whether the evolutionary algorithm evolving developmental timings (EDT) that we previously proposed can be the desired one. The EDT makes some variables values more quickly converge than the remains for any problems, and then, decides values of the remains to obtain a higher fitness value under the fixation of the variables values. In addition, factors to decide which variable values converge more quickly, that is, developmental timings are evolution targets. Simulation results reveal that the EDT has worse performance than the linkage tree genetic algorithm (LTGA), which is one of the state-of-the-art model-based evolutionary algorithms, for decomposable problems and also that the difference in the performance between them becomes smaller for problems with overlaps among linkages and also that the EDT has better performance than the LTGA for problems whose structures are hard to identify. Those results suggest that an appropriate search strategy is different between decomposable problems and those hard to decompose.

DOI： 10.3390/electronics9111866

Scopus

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A test problem with difficulty in decomposing into sub-problems for model-based genetic algorithms 査読有り

Ohnishi K., Ikeda S., Yu T.L.

GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion 221 - 222 2020年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Fully or nearly decomposable problems have been often used as test problems in genetic algorithm (GA) researches. The two types of problems have the common feature that all bits in each sub-problem are used for calculating its fitness value. The present model-based GAs appropriately decompose the whole of such a problem into parts and efficiently solve it. However, so far there has not been a test problem in which sub-problems are overlapped and bits of each sub-problem in the overlapped parts used for calculating a fitness value of the sub-problem vary depending on a bit pattern of a given solution candidate. This type of problems might cause difficulty in the decomposition to model-based GAs. In the study we propose the overlapped chains problem (OCP) as this type of problem. The results of applying several GAs to instances of the OCP show that some model-based GA cannot yield better search performance than a simple operator-based GA.

DOI： 10.1145/3377929.3389993

Scopus

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Motivating Participants in Human-based Evolutionary Computation Systems 査読有り

Watanabe T., Zhu Y., Yoshikawa T., Ohinishi K.

2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings 2020年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Human-based evolutionary computation (humanbased EC), which uses humans as executors of all evolutionary operators, can solve problems for which only humans can judge the quality of solutions. In human-based EC systems, when participants whojoin problem solving are fixed, the upper limit of search performance of the human group should be unpredictable but roughly implicitly decided. Therefore, unlike standard EC using computers, human-based EC systems need to enhance or maintain motivations of participants for contributions to derive better search performance of the group. In the paper, we propose two methods for motivating participants in human-based EC systems. The first method is meant to enhance motivations by differentiating participants. More precisely, it feedbacks rankings on the number of times of producing and evaluating solution candidates to participants in a realtime manner. The second method is meant to maintain motivations by equalizing participants. More precisely, it sets the maximum allowed number of times of producing and evaluating solution candidates equally to all participants. It can also theoretically shorten a time period for problem solving. The two methods are strategically contrary to each other. We reveal though experiments that the first method enhances motivations of participants and also that systems using the second method and not using it produce same quality of solutions. These results suggest that we should feedback another rankings which are not based on the number of times to participants while using the second method to obtain high quality of solutions in a short period of time.

DOI： 10.1109/CEC48606.2020.9185877

Scopus

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勾配方向ヒストグラム特徴量とマハラノビス距離分類器を用いた医療記録の身体部位図認識査読有り

大崎美穂, 佐々木捷人, 川中普晴, 大西圭, 片桐滋

医療情報学 ( 一般社団法人日本医療情報学会 ) 39 ( 6 ) 275 - 290 2020年01月

記述言語：日本語掲載種別：研究論文（学術雑誌）

<p>　一般に手術説明書などの医療記録には，医師が疾患の部位・大きさ・状態などを図示するための身体部位図が含まれる．どの身体部位図が含まれるかは医療記録の管理や知識発見に役立つ重要な情報である．本研究では，身体部位図の種類を自動的に認識する手法の提案開発を目的とする．過去の研究では，改変加重方向指数ヒストグラム特徴量と修正2次識別関数分類器から成る手法を適用し，10種類の身体部位図認識で98.52［％］の認識率を示した．この認識率は比較的高いが向上の余地があり，また，従来手法は処理と設定が複雑，かつ，困難である問題があった．そこで我々は高い性能と簡易な処理と設定を目指し，勾配方向ヒストグラム特徴量とマハラノビス距離分類器から成る手法を提案する．10種類，および，30種類の身体部位図を認識する実験を行った結果，提案手法は大半の条件で100.00［％］の汎化認識率を達成し，従来手法よりも有効であることが示された．</p>

DOI： 10.14948/jami.39.275

CiNii Article

CiNii Research

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Population-based Search Relying on Spatial and/or Temporal Scale-free Behaviors of Individuals 査読有り

Zhang Z., Zhu Y., Fujiwara A., Ohinishi K.

2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 2327 - 2334 2019年12月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We develop two types of simple population-based search algorithms that model two types of scale-free behaviors of individuals. The scale-free behavior is a particular behavior of individuals of species that search for food not cooperatively but independently. One type of the scale-free behaviors is that a moving distance of an individual from the present food source follows a power low distribution, which is called the spatial scale-free behavior. The other is that a staying duration of an individual at the preset food source follows a power low distribution, which is called the temporal scale-free behavior. We assume static and dynamic problems in which a position of the best food source (the global optimum) is not changed and changed, respectively. In addition, we assume a special event that individuals near the best food source are probabilistically eliminated. We compare the two search algorithms and show that they are complementary with respect to suitable problems. Therefore, we develop a search algorithm that initially includes both types of individuals in a population and evolutionarily adaptively increases an appropriate type of individuals in it. The algorithm is shown to be not the best but work quite well for any problems used.

DOI： 10.1109/SSCI44817.2019.9002848

Scopus

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Strawberry optimization for multi-objective knapsack problem 査読有り国際誌

Mizobe Y., Ohnishi K., Fujiwara A.

Proceedings - 2019 7th International Symposium on Computing and Networking Workshops, CANDARW 2019 481 - 483 2019年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In the present paper, we consider multi-objective knapsack problem, which is one of well-known multi-objective optimization problems, and propose an optimization algorithm based on a strawberry algorithm (SBA). The experimental results show that the proposed algorithm obtains a better set of Pareto solutions than the existing algorithm.

DOI： 10.1109/CANDARW.2019.00092

Scopus

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An intuitive and traceable human-based evolutionary computation system for solving problems in human organizations 査読有り国際誌

Ohnishi K., Yoshikawa T., Yu T.L.

GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion 1457 - 1464 2019年07月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Human-based evolutionary computation (EC), for which people act as executors of all evolutionary operators, can be used to solve problems in human organizations. We previously developed a human-based EC system that represents solutions as tags (words) and allows people to evaluate solutions by clicking corresponding tags. Although the system was easy and intuitive to use, it could not handle problems for which solutions are represented as long sentences. In addition, the system could not trace the evolution of solutions. Traceability is a must for the system to be widely and reliably used. In this study, we thus develop a human-based EC system that allows solutions to be represented as both sentences and tags. A function for tracing the evolution of solutions is embedded into the system. The function asks a solution creator to specify which existing solutions influenced the solution creation. We conduct an experiment in which 18 human subjects use the system and then fill out a survey. The results show that the system creates better solutions than those created by each human subject independently. Furthermore, the evolution tree generated from the information given by solution creators is used to confirm that the system allows the evolution of solutions to be traced.

DOI： 10.1145/3319619.3326808

Scopus

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A Metaheuristic Relying on Random Walk on a Graph for Binary Optimization Problems 査読有り国際誌

Sato T., Ohnishi K.

Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 739 - 744 2019年01月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Recently, evolutionary algorithms that can solve decomposable binary problems very efficiently have been developed. They are so-called model-based evolutionary algorithms, which build a model for generating solution candidates by a machine learning technique using a population. Their central procedure is linkage detection that reveals a problem structure, that is, how the entire problem consists of sub-problems. However, the model-based evolutionary algorithms have been shown to be ineffective against problems that are hard to identify their structures. Therefore, metaheuristics including evolutionary algorithms that can solve both problems quickly, reliably, and accurately are required. In this paper, toward realizing such algorithms, we propose a new model-based metaheuristic. It initially forms a graph in which a pair of a position and a value on the string of a solution candidate is a vertex and directed edges are randomly made between vertexes, and then repeats the following three steps: (1) conducting random walk on the graph, (2) producing solution candidates, and (3) reconstructing the topology of the graph. The simulation results show that the proposed metaheuristic is inferior to conventional algorithms against decomposable problems, but superior to conventional ones against problems that are hard to identify their structures.

DOI： 10.1109/SMC.2018.00134

Scopus

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「進化計算シンポジウム2018」特集号の企画にあたって

渡邉真也, 佐藤寛之, 小野景子, 大西圭

進化計算学会論文誌 ( 進化計算学会 ) 10 ( 1 ) 1 - 1 2019年01月

Evolutionary Problem Solving by People Being Aware of Others' Preferences 査読有り国際誌

Matsumoto R., Kanmura M., Ohnishi K., Watanabe S.

2018 9th International Conference on Awareness Science and Technology, iCAST 2018 26 - 31 2018年10月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Interactive and human-based evolutionary computation methods both enable people to solve a given problem together, but it is hard for us to analyze the processes of the problem solving because people interact with each other nonlinearly in the methods. Therefore, studies of those evolutionary methods are likely to be practical. To make such evolutionary methods involving people more widely used, they need to be traceable and obtain more trust from users. So, in this study, we develop a new traceable evolutionary method involving people. In the method, two or more people produce and evaluate solutions in turn one by one, while being aware of the preferences of each other. In addition, assuming two people solve a problem together, we construct not only an experimental system for the method but also asimulation model of the experimental system. Then, we obtain results of experiments by human subjects and simulations and realize from the results that the simulation results assuming completely rational people are different from the experimental ones, in which cooperation beyond rationality among people can occur.

DOI： 10.1109/ICAwST.2018.8517250

Scopus

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The human-based evolutionary computation system enabling us to follow the solution evolution 査読有り国際誌

Fujimoto K., Ohnishi K., Yoshikawa T.

GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion 39 - 40 2018年07月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Human-based evolutionary computation (HBEC) is evolutionary computation in which agents of implementing evolutionary operators are multiple humans and can solve problems in our human society, where only humans can judge the qualities of their solutions. In this study we add a new function that enables us to follow the solution evolution to our previously developed HBEC system, in which a tag cloud is used as a place for the solution evolution. Also, we show the usability and the traceability of the HBEC system through an experiment.

DOI： 10.1145/3205651.3208764

Scopus

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Designing fitness functions for evolutionary optimization of the system inspired by pattern formation in morphogenesis 査読有り国際誌

Ohnishi K.

Proceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018 255 - 260 2018年07月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

The morphogenetic engineering that learns biological morphogenesis has attracted our attention recently. In the paper, we first propose a new system that models pattern formation in biological morphogenesis. The system is theoretically able to produce a variety of shapes similar to desired one. However, to realize that, it is necessary to optimize parameters of the system. So, we assume the use of an evolutionary algorithm for the optimization and examine a suitable fitness function for the optimization through simulations. The simulation results reveal that the suitable fitness function enables the evolutionary algorithm to find parameters that produce a variety of rough shapes including the desired one at the top priority and then to conduct fine-tuning of parameters for obtaining closer shapes to the desired one.

DOI： 10.1109/SCIS-ISIS.2018.00053

Scopus

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Parallel Evolutionary Peer-to-Peer Networking in Realistic Environments 査読有り国際誌

Ohnishi K.

Applied Computational Intelligence and Soft Computing 2017 2017年01月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

In the present paper we first conduct simulations of the parallel evolutionary peer-to-peer (P2P) networking technique (referred to as P-EP2P) that we previously proposed using models of realistic environments to examine if P-EP2P is practical. Environments are here represented by what users have and want in the network, and P-EP2P adapts the P2P network topologies to the present environment in an evolutionary manner. The simulation results show that P-EP2P is hard to adapt the network topologies to some realistic environments. Then, based on the discussions of the results, we propose a strategy for better adaptability of P-EP2P to the realistic environments. The strategy first judges if evolutionary adaptation of the network topologies is likely to occur in the present environment, and if it judges so, it actually tries to achieve evolutionary adaptation of the network topologies. Otherwise, it brings random change to the network topologies. The simulation results indicate that P-EP2P with the proposed strategy can better adapt the network topologies to the realistic environments. The main contribution of the study is to present such a promising way to realize an evolvable network in which the evolution direction is given by users.

DOI： 10.1155/2017/4169152

Scopus

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Simple linkage identification using genetic clustering 査読有り国際誌

Ohnishi K., Ahn C.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10593 LNCS 373 - 384 2017年01月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

The paper proposes a simple linkage identification method for binary optimization problems. The method is basically equivalent to the genetic clustering method, called GC, inspired by the speciation due to segregation distortion genes that was previously proposed by us. A genetic algorithm using the method, called GAuGC, is also proposed. The GAuGC is applied to decomposable, nearly decomposable, and indecomposable problems. The results show that the GAuGC better solves problems with weak decomposability than the linkage tree genetic algorithm for comparison and also show that it cannot handle the deception well.

DOI： 10.1007/978-3-319-68759-9_31

Scopus

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Building a simulation model for distributed human-based evolutionary computation 査読有り国際誌

Ohnishi K., Okano J., Koeppen M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10385 LNCS 40 - 49 2017年01月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Evolutionary computation (EC) is called “human-based EC” especially when its all main operators, which are selection, crossover, and mutation, are executed by humans. One type of human-based EC is distributed human-based EC, in which humans independently manage their solution candidates and share them by direct communication between the humans. It is expected that the EC solves problems in human organizations. However, it is not easy to conduct real experiments to investigate the effect of human behaviors on the performance of the EC because such experiments needs many cooperative people. In the paper, we, therefore, first model human behaviors and then build a simulation model including the model. The model of human behaviors focuses on physical movement and free will to decide a time of interactions with others. Furthermore, we attempt to understand the EC though simulations using the built simulation model.

DOI： 10.1007/978-3-319-61824-1_5

Scopus

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A Generation Gap Model for a Human-Based Evolutionary Algorithm Using a Tag Cloud 査読有り国際誌

Azumaya M., Ohnishi K.

Proceedings - 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems and 2016 17th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2016 880 - 885 2016年12月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We previously proposed a human-based evolutionary algorithm (human-based EA) that used a tag cloud, and in this paper, we propose a generation gap model for the human-based EA. In the previous model, people created candidate solutions, and the created candidate solutions were displayed as tags in a tag cloud. People then evaluated the candidate tags, and those with the greatest fitness were displayed using a larger font size. However, in the previous model, there was a limit on the number of tags that could be displayed in the tag cloud, and after that number had been reached, if new tags were created, they would not be included. Therefore, we propose a generation gap model for solving this problem by allowing each subsequent generation to include all of the tags from the previous generation that have a fitness level that is greater than a given threshold. The remainder in the tag cloud are replaced by tags in a queue for storage that were created before and have never displayed. We carried out an experiment using the human-based EA with the generation gap model, and the results showed that almost all participants believed the tags created by our system were better than those that they would have created by themselves.

DOI： 10.1109/SCIS-ISIS.2016.0191

Scopus

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Non-swarm intelligence search algorithm based on the foraging behaviors of fruit flies 査読有り国際誌

Ohnishi K., Fujiwara A., Koeppen M.

2016 IEEE Congress on Evolutionary Computation, CEC 2016 1509 - 1516 2016年11月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In the present study, we examine the foraging behavior of the fruit fly (Drosophila), which unlike social insects, independently and autonomously forages. Moreover, we propose a new population-based, non-swarm intelligence search algorithm that mimics the foraging behaviors of fruit flies. We find that the time that a fruit fly stays in a food source region follows a power-law. A power-law distribution satisfies the scale-free property, so the observed behaviors of fruit flies can be called scale-free behaviors, which are modeled by the proposed algorithm. We examine the effect of scale-free behaviors on search performance by applying the proposed algorithm to 28 test functions with two real parameters. The results reveal that the scale-free property is related to a balance between exploration and exploitation and affects the search performance. Moreover, particular parameter values for fixing the scale-free property yield a better search performance for most of the test functions considered herein. The present paper does not provide a competent search algorithm for solving static optimization problems, but rather introduces a novel temporal property of individual behaviors, i.e., a scale-free property, which is expected to provide a new way to think about search algorithms.

DOI： 10.1109/CEC.2016.7743968

Scopus

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Visualizing self- and peer-assessment data by a self-organizing map for inducing awareness in learners 査読有り国際誌

Ueki Y., Ohnishi K.

International Journal of Computer Information Systems and Industrial Management Applications 8 23 - 32 2016年01月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

Self- and peer-assessments among learners are presumed to motivate learners to increase their learning and introspection. The basis behind this effect is the awareness resulting from differences between a self-assessment result and the assessment results from others. Therefore, to enable learners to benefit from self- and peer-assessments, we need to easily visualize results that make them aware of some factor that could improve their learning ability. In this study, we designed a system to visualize self- and peer-assessment data, which are many and multi-dimensional data, in such a way that we can easily grasp an overview at first glance. We then developed an actual system using a self-organizing map (SOM) as a method for visualizing self- and peer-assessment data. In a comparison of the visualization method in our developed system, SOM, and a conventional method, a radar chart, we showed the usefulness of our visualization method, SOM, through a subjective evaluation test and a statistical hypothesis test. In addition, we carried out an experiment in which people wrote reports, then conducted self- and peer-assessments of what they wrote by using the developed system. The experimental results showed that the visualization of self- and peer-assessment data enabled people to become aware of some factor that helped them to improve their reports.

Scopus

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自己組織化マップを用いた相互評価可視化システムのプレゼンテーションスキル育成への応用

植木勇太, 大西圭

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 32 ( 0 ) 407 - 412 2016年01月

協調型インタラクティブ進化計算実行チームの形成支援システム

大西圭, 栗栖万理子, 佐藤太河, 高木英行

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 32 ( 0 ) 231 - 236 2016年01月

分散型人間ベース進化計算のシミュレーションモデル構築

大西圭, 岡野純也

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 32 ( 0 ) 225 - 230 2016年01月

印象地図を用いる観光地検索システム

中村達哉, 吉満阿弥, 大西圭

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 31 ( 0 ) 490 - 495 2015年01月

担当区分：最終著者,　責任著者記述言語：日本語掲載種別：研究論文（研究会，シンポジウム資料等）

近年，日本を訪れる外国人旅行者が増加している．しかし，ガイドブックによる紹介が少ないエリアに外国人旅行者を呼び込むことは容易ではない．一方，そのようなエリアに行きたいと思う外国人旅行者は，インターネット上で情報収集が可能であるが，多言語で書かれた情報を機械的に翻訳した際には精度の問題があるだろう．そこで本研究では，外国人にも直感的に理解できる，観光地に対する印象を示した地図を用いる検索システムを提案する．具体的には，複数の旅行者による複数の観光地に対する印象データを，自己組織化マップを用いて可視化して印象地図を作る．さらに，システムの利用者に使用感等のアンケートを実施することで，システムの基本的な有用性を示し，改善点を明らかにする．

DOI： 10.14864/fss.31.0_490

CiNii Article

CiNii Research

遺伝的クラスタリング手法を用いた創発型画像生成

坂戸響, 大西圭

日本知能情報ファジィ学会ファジィシステムシンポジウム講演論文集 ( 日本知能情報ファジィ学会 ) 31 ( 0 ) 681 - 686 2015年01月

担当区分：最終著者,　責任著者記述言語：日本語掲載種別：研究論文（研究会，シンポジウム資料等）

自然界の多くの構造は，単純な構造を持った構成要素間の局所的な非線形の相互作用によって形成されている．このような構造形成は，人工生命分野において「創発」と呼ばれている．創発型の構造形成の利点は，単純な構造から予想できない複雑な構造が生まれることである．一方で，最終構造がどのようになるかを予想することが困難という欠点がある．本研究では，所望の構造と幾分か類似する多彩な新奇構造を生成可能な創発型構造生成手法を提案する．さらに，その方法の考え方に従う画像生成手法を具体的に実現する．その手法は，与えられた画像の一部の画素データに対して遺伝的クラスタリング手法を適用して，その画像にある程度類似する多彩な画像を生成する．

DOI： 10.14864/fss.31.0_681

CiNii Article

CiNii Research

Self-configuration of Wireless Access Points Based on Mechanisms of Biological Development and Evolution 査読有り

Kei Ohnishi,Kazuya Tsukamoto,Shigeru Kashihara,Yuji Oie

Self-Adaptive Networking (SAN) Workshop 2010年10月

Evolutionary Creation of Linkages between Information Sources in P2P Networks 査読有り

Kei Ohnishi,Takeshi Yamaura,Yuji Oie

World Automation Congress (WAC 2010) 2010年09月

Information Sharing with Identifiers Representing Human Interests in Wireless Ad-hoc Networks 査読有り

Kei Ohnishi,Kazuya Tsukamoto,Shinya Yamamura,Akira Nagata,Masato Tsuru

International Seminar on Intelligent Systems 2010年09月

Access Load Balancing with Analogy to Thermal Diffusion for Dynamic P2P File-Sharing Environments 査読有り

Masanori Takaoka,Masato Uchida,Kei Ohnishi,Yuji Oie

IEICE Transactions on Communications E93-B ( 5 ) 1140 - 1150 2010年05月

Dynamic and Decentralized Storage Load Balancing with Analogy to Thermal Diffusion for P2P File Sharing 査読有り

Masato Uchida,Kei Ohnishi,Kento Ichikawa,Masato Tsuru,Yuji Oie

IEICE Transactions on Communications E93-B ( 3 ) 525 - 535 2010年03月

Evolutionary P2P Networking that Fuses Evolutionary Computation and P2P Networking Together 査読有り

Kei Ohnishi,Yuji Oie

IEICE Transactions on Communications E93-B ( 2 ) 317 - 328 2010年02月

Folksonomical P2P File Sharing Networks Using Vectorized KANSEI Information as Search Tags 査読有り

Kei Ohnishi,Kaori Yoshida,Yuji Oie

IEICE Transactions on Information and Systems E92-D ( 12 ) 2402 - 2415 2009年12月

Complex Routing for Temporary Information Sharing in Wireless Mesh Networks 査読有り

Takeshi Koga,Kei Ohnishi,Kazuya Tsukamoto,Yuji Oie

The second International Workshop on Information Network Design (WIND'09) 2009年11月

Pattern Formation in Networks Inspired by Biological Development 査読有り

Kei Ohnishi,Kaori Yoshida,Mario Koeppen

International Conference on Arts & Technology (ArtsIT 2009) 2009年09月

Evolutionary P2P Network Adaptively Changing Its Topologies for Reliable Searching 査読有り

Kei Ohnishi,Kento Ichikawa,Yuji Oie

Workshop on Bio-Inspired Algorithms for Distributed Systems (BADS 2009) 2009年06月

Evolutionary P2P Networking for Enhancing Search Performance 査読有り

Kei Ohnishi,Kento Ichikawa,Yuji Oie

Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2008) 2008年09月

Designing Redundancy Toward Building Easily Manageable Wireless Sensor Networks for Humans 査読有り

Kei Ohnishi,Hitomi Tamura,Kazuya Tsukamoto,Yuji Oie

The Second International Conference on Sensor Technologies and Applications (SENSORCOMM 2008) 2008年08月

Thermal Diffusion-based Access Load Balancing for P2P File Sharing Networks 査読有り

Masanori Takaoka,Kei Ohnishi,Masato Uchida,Yuji Oie

The First International Workshop on Computational P2P Networks: Theory & Practice (ComP2P 2008) 2008年08月

Query-Trail-Mediated Topology Reconstruction for Exploring Performance Trade-off in Unstructured P2P Networks 査読有り

Kei Ohnishi,Satoshi Nagamatsu,Yuji Oie

International Journal of Hybrid Intelligent Systems 5 97 - 108 2008年06月

Evolution and Learning Mediated by Difference in Developmental Timing 査読有り

Kei Ohnishi,Masato Uchida,Yuji Oie

Journal of Advanced Computational Intelligence and Intelligent　Informatics (JACIII) 11 ( 8 ) 905 - 913 2007年10月

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