著者
目良 和也 市村 匠 相沢 輝昭 山下 利之
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.17, no.3, pp.186-195, 2002 (Released:2002-04-04)
参考文献数
31
被引用文献数
6 21

There have been some studies about spoken natural language dialog,and most of them have successfully been developed within the speci ed task domains. However,current human-computer interfaces only get the data to process their programs.If the dialog processing has emotion comprehensive faculties, it should lead us to more human-like performance.In this paper,we present a method for constructing an emotion-handling dialog system in order to facilitate more confortable interaction with the users. We describe how to calculate emotions from the utterances,focusing on the similarities between the grammar structures and the semantic structures within the case frame.We made emotion generating calculations(EGC)to generate pleasure/displeasure emotion from an event.We also calculate the degree of the pleasure/displeasure from an opposite angle's length of the rectangular parallelepiped consisting of the all the terms in the EGC.EGC uses 8 type calculations for 12 event classi ed type by Okada. Word impressions about like/dislike are used for their calculations.Furthermore,we apply these calculations to the negatives and the noun phrases.To verify the e ectiveness of the proposed method,we tested some conversations using WWW-based health service system for elderly. We applied our method to 80 event in the conversations and calculated emotions almost corresponded to human-generating emotions.
著者
秋元 泰介 小方 孝
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.31, no.6, pp.AI30-O_1-8, 2016-11-01 (Released:2017-05-30)
参考文献数
54

Creativity is a challenging topic for artificial intelligence (AI) from the perspectives of both science and engineering. For engineering purposes, the manner in which creative AI systems provide values to humans and societies is a major concern that should be examined for the future development of AI technologies. The broader purpose of this study is to present a new direction of designing creative AI systems that consider their relationship with humans. We thus propose the basic design and concepts of a co-creative narrative generation system that produces diverse narratives through continual narrative generating chain reactions involving many agents. These agents include narrative generation programs and human narrative creators. The characteristics and significance of this design are discussed from several perspectives: 1) the relationship between generative programs and humans, 2) the design direction of narrative creativity, 3) the architectural aspect of a co-creative system for integrating many generative agents, and 4) knowledge construction in the narrative co-creation cycle.
著者
濱口 拓男 大岩 秀和 新保 仁 松本 裕治
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.33, no.2, pp.F-H72_1-10, 2018-03-01 (Released:2018-04-03)
参考文献数
31
被引用文献数
5

Knowledge base completion (KBC) aims to predict missing information in a knowledge base. In this paper, we address the out-of-knowledge-base (OOKB) entity problem in KBC: how to answer queries concerning test entities not observed at training time. Existing embedding-based KBC models assume that all test entities are available at training time, making it unclear how to obtain embeddings for new entities without costly retraining. To solve the OOKB entity problem without retraining, we use graph neural networks (GNNs) to compute the embeddings of OOKB entities, exploiting the limited auxiliary knowledge provided at test time. The experimental results show the effectiveness of our proposed model in the OOKB setting. Additionally, in the standard KBC setting in which OOKB entities are not involved, our model achieves state-of-the-art performance on the WordNet dataset.
著者
海野 一則 菊地 剛正 國上 真章 山田 隆志 寺野 隆雄
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.33, no.4, pp.E-HB3_1-9, 2018-07-01 (Released:2018-07-02)
参考文献数
16

This research has two objectives: (1) to model the momentum effect, (2) to propose a portfolio selection algorithm MESPSA that can use the momentum effect to obtain excess profit. The momentum effect is a phenomenon in which stocks that rise (decline) tend to continue to rise (decline), and momentum effect is a phenomenon often seen in the stock market. However, because existing research does not separate momentum effects from stock price fluctuations it is not always possible to obtain excess return when working with an unknown data set that contains a momentum effect. In this research, we define a new External Force Momentum Effect (EFME) model based on bias in stock price rises (declines). We prepare an artificial data set that contained this momentum effect and construct a portfolio with the proposed algorithm. The relationship between the EFME model and excess return is then analyzed to verify that excess profit can be obtained. Also, we confirm that the proposed algorithm for the actual stock price data set yields excess profits.
著者
大澤 昇平 松尾 豊
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.31, no.2, pp.A-F24_1-10, 2016

Success of software developping project depend on skills of developers in the teams, however, predicting such skills is not a obvious problem. In crowd sourcing services, such level of the skills is rated by the users. This paper aims to predict the rating by integrating open source software (OSS) communities and crowd soursing services. We show that the problem is reduced into the feature construction problem from OSS communities and proposes the <i>s</i>-index, which abstract the level of skills of the developers based on the developed projects. Specifically, we inetgrate oDesk (a crowd sourcing service) and GitHub (an OSS community), and construct prediction model by using the ratings from oDesk as a training data. The experimental result shows that our method outperforms the models without <i>s</i>-index for the aspect of nDCG.
著者
長谷川 禎彦 伊庭 斉志
出版者
The Japanese Society for Artificial Intelligence
雑誌
人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)
巻号頁・発行日
vol.22, pp.37-47, 2007-11-01
参考文献数
34
被引用文献数
1 4

Genetic Programming (GP) is a powerful optimization algorithm, which employs the crossover for genetic operation. Because the crossover operator in GP randomly selects sub-trees, the building blocks may be destroyed by the crossover. Recently, algorithms called PMBGPs (Probabilistic Model Building GP) based on probabilistic techniques have been proposed in order to improve the problem mentioned above. We propose a new PMBGP employing Bayesian network for generating new individuals with a special chromosome called <I>expanded parse tree</I>, which much reduces a number of possible symbols at each node. Although the large number of symbols gives rise to the large conditional probability table and requires a lot of samples to estimate the interactions among nodes, a use of the expanded parse tree overcomes these problems. Computational experiments on two subjects demonstrate that our new PMBGP is much superior to prior probabilistic models.
著者
岩澤 有祐 矢入 郁子 松尾 豊
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.4, pp.A-GB5_1-12, 2017-07-01 (Released:2017-08-17)
参考文献数
23

This paper proposes a novel neural networks based model for learning user-independent features. In activity recognition using wearable sensors, user-independence of features could provide better user-generalization performance, enhance privacy protection, and both are important for using activity recognition techniques in a real-world scenario. However, designing such features is not an easy task, because it is not clear what kind of features become user-independent, and moreover, poor design of user-independence harms activity recognition performance.Hear, we propose User-Adversarial Neural Networks for automatically learning user-independent features. The proposed model considers an adversarial-user classifier in addition to a regular activity classifier in the training phase, and learn the features that help to distinguish the activities but obstruct to distinguish the users. In other words, the model explicitly penalizes representations for becoming user-dependent, while keeping activity recognition performance as much as possible. Our main result is an empirical validation on three activity recognition tasks regarding wearable sensor based activity recognition. The result shows the proposed model improves independence of features comparing with the regular deep convolutional neural networks in both qualitatively and quantitively. We also summarize future work for better user-generalization and privacy protection from the perspective of the representation learning.
著者
ジメネス フェリックス 吉川 大弘 古橋 武 加納 政芳 中村 剛士
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.5, pp.A-H11_1-11, 2017-09-01 (Released:2017-09-01)
参考文献数
19
被引用文献数
1

The growth of robot technology has prompted growing interest in educational-support robots that assist in learning. Most of these studies report on collaborative learning between educational-support robots and healthy children. Meanwhile, the number of children in primary schools with diagnosed developmental disabilities (gray zone children) has increased in Japan. Gray zone children may have difficulty learning over long time periods. Moreover, gray zone children tend to receive peer teaching from healthy children in the school environment. Other symptoms of autism in children are low self-esteem and possibly depression. We expect that gray zone children will learn best by teaching another learner. Learning-by-teaching promotes self-esteem and improves the learning time. In a previous study, a robot that answered a question incorrectly and uttered “Please teach me” or similar statements provided a collaborative learning environment for the learning-by-teaching method. However, whether collaborative learning with this robot increases the learning time of gray zone children was not investigated. Therefore, the present study investigates whether gray zone children can improve their learning time in collaborative learning with a robot that prompts learning-by-teaching. The robot is designed to answer questions incorrectly and utter statements such as “Please teach me.” The robot is also designed to have learning capability. For example, the robot learns the methods of problem-solving from its human partner. Thus, when presented with a question that can be solved by a previously learned method, the robot can answer the question correctly. The experimental results suggested that the learning enhancement was driven by the robot’s initial incapacity to answer a question, and its requests for assistance by the gray zone child. Gray zone children engaged in collaborative learning with our robot spent more time learning than those working alone. Moreover, the gray zone children enjoyed the collaborative learning with our robot than the robot which always solves questions correctly and never solves questions correctly.
著者
森 純一郎 松尾 豊 石塚 満
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.20, no.5, pp.337-345, 2005 (Released:2005-08-02)
参考文献数
28
被引用文献数
4 13

With the currently growing interest in the Semantic Web, personal metadata to model a user and the relationship between users is coming to play an important role in the Web. This paper proposes a novel keyword extraction method to extract personal information from the Web. The proposed method uses the Web as a large corpus to obtain co-occurrence information of words. Using the co-occurrence information, our method extracts relevant keywords depending on the context of a person. Our evaluation shows better performance to other keyword extraction methods. We give a discussion about our method in terms of general keyword extraction for the Web.
著者
松井 藤五郎
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.26, no.2, pp.330-334, 2011 (Released:2011-01-06)
参考文献数
12
被引用文献数
2

This paper describes a reinforcement learning framework based on compound returns, which is called compound reinforcement learning. Compound reinforcement learning maximizes the compound return in returns-based MDPs. We also describe compound Q-learning algorithm. We present experimental results using an ilustrative example, 2-armed bandit.
著者
中山 浩太郎 伊藤 雅弘 ERDMANN Maike 白川 真澄 道下 智之 原 隆浩 西尾 章治郎
出版者
The Japanese Society for Artificial Intelligence
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.24, no.6, pp.549-557, 2009
被引用文献数
3 4

Wikipedia, a collaborative Wiki-based encyclopedia, has become a huge phenomenon among Internet users. It covers a huge number of concepts of various fields such as arts, geography, history, science, sports and games. As a corpus for knowledge extraction, Wikipedia's impressive characteristics are not limited to the scale, but also include the dense link structure, URL based word sense disambiguation, and brief anchor texts. Because of these characteristics, Wikipedia has become a promising corpus and a new frontier for research. In the past few years, a considerable number of researches have been conducted in various areas such as semantic relatedness measurement, bilingual dictionary construction, and ontology construction. Extracting machine understandable knowledge from Wikipedia to enhance the intelligence on computational systems is the main goal of "Wikipedia Mining," a project on CREP (Challenge for Realizing Early Profits) in JSAI. In this paper, we take a comprehensive, panoramic view of Wikipedia Mining research and the current status of our challenge. After that, we will discuss about the future vision of this challenge.
著者
池上 高志 岡 瑞起 橋本 康弘
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.30, no.6, pp.811-819, 2015-11-01 (Released:2017-09-07)
参考文献数
24

The Web is perhaps the most complex system that we know today. Its massive scale, complex dynamism, open richness, and social character mean that it may be more profitable to study it by using tools and concepts appropriate for understanding nervous systems, organisms, ecosystems and society, rather than approaches more traditionally employed to study engineering technology. Simultaneously, the scientists trying to understand this wide array of complex natural systems may have much to gain by considering the emerging study of the Web. In this paper, taking examples from our recent studies on the Web, we concretely discuss the relevance of the Web as a large model, as opposed to small models often used in physics or biology, for understanding living systems. An idea is forwarded of a default mode network that introduces autonomy, evolvability and homeostasis into the Web. For example, we argue for the existence of two modes of the states in Twitter; the excitation and baseline. The Web turns out to be an excitable media similar to a brain or certain kinds of chemical systems. R. Ashby's laws of requisite variety is also revisited to study its relevance in the light of controlling complex systems.
著者
芦川 将之 川村 隆浩 大須賀 昭彦
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.3, pp.B-G81_1-13, 2017-05-01 (Released:2017-05-01)
参考文献数
31

Current crowdsourcing platforms such as Amazon Mechanical Turk provide an attractive solution Crowdsourcing platforms provide an attractive solution for processing numerous tasks at a low cost. However, insufficient quality control remains a major concern. Therefore, we developed a private crowdsourcing system that allows us to devise quality control methods. In the present study, we propose a grade-based training method for workers in order to avoid simple exclusion of low-quality workers and shrinkage of the crowdsourcing market in the near future. Our training method utilizes probabilistic networks to estimate correlations between tasks based on workers’ records for 18.5 million tasks and then allocates pre-learning tasks to the workers to raise the accuracy of target tasks according to the task correlations. In an experiment, the method automatically allocated 31 pre-learning task categories for 9 target task categories, and after the training of the pre-learning tasks, we confirmed that the accuracy of the target tasks was raised by 7.8 points on average. This result was comparatively higher than those of pre-learning tasks allocated using other methods, such as decision trees. We thus confirmed that the task correlations can be estimated using a large amount of worker records, and that these are useful for the grade-based training of low-quality workers.
著者
西岡 伸 鳥居 拓馬 楠本 拓矢 松本 渉 和泉 潔
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.5, pp.AG16-C_1-10, 2017-09-01 (Released:2017-09-01)
参考文献数
20

In recent financial market, high frequency traders (HFTs) and dark pools have been increasing their share. Financial analysts have speculated that they might decrease market transparency and malfunction price discovery, and their interaction would make the situation worse.To validate speculations, artificial market simulation is a tool of study by constructing virtual markets on computers. In this research, by constructing an artificial market simulation, we analyzed how the interaction between HFTs and a dark pool impacts on the market efficiency (in the sense of price discovery) of a (lit) stock market. In simulations, two types of trader agents enter the market. A market maker agent, a representative strategy of HFTs, submit orders to the lit market. We analyzed the market maker's interest rate spread, or simply the spread, as a key parameter for their strategy. Stylized trader agents submit orders to either the lit market or the dark pool with some probability given as a parameter.The simulation results suggest that on the condition that market makers have little impact to market pricing (having a large spread), moderate use of dark pools can promote market pricing. On the other hand, on the condition that market makers have big impact to market pricing, excessive use of dark pools can inhibit market pricing, while using dark pools do not have bad influence when the rate of use is not high. On the influence of market makers, our results suggest that the bigger the impact to market pricing (a small spread), the more it can promote market pricing.
著者
林 勇吾
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.4, pp.E-G91_1-9, 2017-07-01 (Released:2017-07-03)
参考文献数
24

The present study investigated the influence of reflections on self/others’ trust within group-based problem solving. The study assessed the role of trust dynamics on perspective-taking activities within conflictive groups, extending the experimental framework used by a previous study and including conversational agents for controlling participants’ interactions related to trust dynamics and perspective taking behavior. Results showed that (1) reflections of self/other trust in conflictive groups may influence trust towards other members, and (2) reflections of trust by members with conflicting perspectives may facilitate trust and perspective taking process. This suggests that the level of trust dynamics facilitates trust and can function to manifest perspective taking within cooperative groups. The results of the study provide new knowledge in collaborative problem solving studies that the development of trust has a progressive effect on perspective taking activities among conflictive members.
著者
河野 慎 植田 一博
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.1, pp.WII-E_1-8, 2017-01-06 (Released:2017-01-20)
参考文献数
23

People collect and use information about real world from internet to help their daily activities. In particular, the number of users in microblog such as Twitter is so large that users can get a diversity of information. They can elicit not only the information which they need from microblog posts but also the location which is indicated by the contents posted in microblog. While previous approaches apply corpus-based or machine learning that require various prior knowledge such as natural language processing and feature engineering, our approach is able to estimate the location without those requirements with extension of long-short term memory (LSTM). In our experiment, we apply our approach to geo-tagged tweets posted in Twitter and show that this approach is effective in outperforming corpus-based and previous works that use support vector machine (SVM) with bag-of-words (BoW).
著者
野間口 大 下村 芳樹 冨山 哲男
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.20, no.1, pp.11-24, 2005 (Released:2005-01-05)
参考文献数
29
被引用文献数
4 5

In this paper, we report the development of a design knowledge management system, called DDMS (Design Documentation Management System). By composing design documents during design, DDMS encourages a designer to externalize his/her knowledge and facilitates sharing and reuse of such externalized design knowledge in later stages. DDMS works as a front end to KIEF (Knowledge Intensive Engineering Framework), which we have been developing over years. DDMS is capable of guiding designers with design process knowledge based on a model of synthesis, combined together with KIEF that can integrate multiple design object models, and maintain consistency among these models. DDMS automatically generates design documents after analyzing design log data based on the model of synthesis. We also illustrate an example of laser lithography design to demonstrate the features of DDMS.
著者
新田 克己 柴崎 真人 安村 禎明 長谷川 隆三 藤田 博 越村 三幸 井上 克巳 白井 康之 小松 弘
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.17, no.1, pp.32-43, 2002 (Released:2002-04-04)
参考文献数
23

We present an overview of a legal negotiation support system, ANS (Argumentation based Negotiation support System). ANS consists of a user interface, three inference engines, a database of old cases, and two decision support modules. The ANS users negotiates or disputes with others via a computer network. The negotiation status is managed in the form of the negotiation diagram. The negotiation diagram is an extension of Toulmin’s argument diagram, and it contains all arguments insisted by participants. The negotiation protocols are defined as operations to the negotiation diagram. By exchanging counter arguments each other, the negotiation diagram grows up. Nonmonotonic reasoning using rule priorities are applied to the negotiation diagram.
著者
新美 潤一郎 星野 崇宏
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.2, pp.B-G63_1-9, 2017-03-01 (Released:2017-03-01)
参考文献数
25
被引用文献数
3

Nowadays, along with the popularity of E-Commerce, the marketing strategy of retail stores has been more complicated with O2O or Omni-channel. Therefore, Customer Relationship Management (CRM) is one of the important issue for the retail stores. It can be difficult to predict customers future behavior with the simple quantitive information such as purchase frequency since each customers are widely diversified. Although the company can obtain the variety of customers information from their online activity, the use of access history is still limited. In this paper, we defined “the variety of user access patterns” collected from their web browsing history and it shows the patterns they visit the website. Finally, we verified its effectiveness with developing a DNN model to predict customers future behavior.
著者
伊藤 詩乃 田中 佑岳 狩野 芳伸 榊原 康文
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.2, pp.F-AI30Ge_1-10, 2017-03-01 (Released:2017-03-01)
参考文献数
22

31 巻6 号AI30-G(2016 年)の論文において、本文引用箇所がすべて[?]として公開されているため、正しい情報を次ページより掲載します.