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Reward Function Using Inverse Reinforcement Learning and Fuzzy Reasoning

Reward Function Using Inverse Reinforcement Learning and Fuz...

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international Symposium on Soft computing and intelligent Systems (SCIS)

作者： Yuta Kato Masayoshi Kanoh Tsuyoshi Nakamura Graduate School of Engineering Chukyo University Nagoya Japan School of Engineering Chukyo University Nagoya Japan Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

A reward function estimated with inverse reinforcement learning has been used to determine a method for controlling a robot. Inverse reinforcement learning requires observed sequences of actions to estimate a reward function. Few models of the sequences give the optimal motion of the robot; therefore, a suboptimal one may be given. However, the suboptimal sequences include some errors and ambiguities. In this paper, we propose a method for quantifying the ambiguity of the reward function, which is designed with inverse reinforcement learning using fuzzy reasoning.

关键词： Reinforcement learning Safety Robots Fuzzy reasoning Mathematical model Trajectory Security

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Design and Implementation of Autonomous Collaboration System of Smart Things using accumulated Experience knowledge 21

Design and Implementation of Autonomous Collaboration System...

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21st international conference on Advanced Communication technology (ICACT)

作者： Lee, Chang-Su Cheung, Sweung-Won Joo, Seong-Soon Kahng, Hyun-Kook Korea Univ Dept Elect & Informat Engn Seoul South Korea Hanwha Techwin Co Ltd Pankyo City South Korea Elect & Telecommun Res Inst Daejeon South Korea

ISBN: (纸本)9791188428021

With the advent of many IoTs, users need a common use environment to easily connect, search, and share various IoTs. In addition, as IoTs become increasingly intelligent, there is a growing demand for services that work together. However, a large number of IoTs can cause serious traffic to the network when they collaborate with each other in a common usage environment. In this paper, we have designed the structure of IoT to construct a distributed social network based on semantic web to solve this problem. We also designed and implemented an autonomous collaborative service of IoT that can find collaborative partners through social network and accumulate experience knowledge after collaboration. We defined IoT with this structure as Smart Thing and a unique Basic Identity Information (BII) that allows Smart Thing to identify each other. In addition, we defined Basic Response Rules (DRRFS) for Smart Thing to follow in the Query & Answer process for Collaboration. Smart Thing with basic identity information is an independent, autonomous IoT device. Smart Thing with a distributed social network finds collaborative partners though recursive queries and provides services. In addition, we have confirmed in the autonomous collaborative system that Smart Thing who has experienced collaborations can work faster and more accurately using the accumulated experience knowledge when the same thing is done again. If all IoTs have basic identity information and use semantic technology, the Internet will be a huge space where Smart Thing can collaborate.

关键词： Autonomous Collaboration System Semantic Web WebID distributed social network IoT device

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A study on Reinforcement-learning Agents with Personality through the Implementation of Character Parameters

A Study on Reinforcement-learning Agents with Personality th...

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international Symposium on Soft computing and intelligent Systems (SCIS)

作者： Daichi Ando Shino Iwashita Graduate School of Bionics Computer and Media Sciences Tokyo University of Technology Tokyo Japan School of Computer Science University of Technology Tokyo Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

We aim to achieve characteristic action in reinforcement-learning agents. Agents with different personality parameters move through a maze with the aim of reaching a goal while obtaining rewards. Three types of parameters are defined: A: Prioritize additional rewards, S: Prioritize goal, and G: Prioritize search rewards. We trained a reinforcement-learning agent with parameters that correspond to a character. statistical information of the learning process of agents were obtained by using TensorBoard and compared. As a result, the agents did not show any personality traits in their behavior. However, we confirmed that the learning process changed depending on the parameter setting pattern.

关键词： Artificial intelligence Training Convergence Optimization Task analysis Surfaces Search problems

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Adapting the Learning Rate of the Learning Rate in Hypergradient Descent

Adapting the Learning Rate of the Learning Rate in Hypergrad...

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international Symposium on Soft computing and intelligent Systems (SCIS)

作者： Kazuma Itakura Kyohei Atarashi Satoshi Oyama Masahito Kurihara Graduate School of Information Science and Technology Hokkaido University Sapporo Hokkaido Japan Faculty of Information Science and Technology Hokkaido University Sapporo Hokkaido Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

Gradient descent is a widely used optimization method. The adjustment of the learning rate is an important factor in improving its performance, and many researchers have investigated methods for automatically adjusting the learning rate. One such method, hypergradient descent, automatically adjusts the learning rate by using gradient descent. However, it introduces the “learning rate of the learning rate,” and an appropriate value for the learning rate of the learning rate must be chosen in order to effectively adjust the learning rate. We investigated the use of two datasets and two optimization methods for doing this and achieved an effective adjustment of the learning rate when the objective function was convex and L-smooth.

关键词： Training Mathematical model Optimization methods Machine learning Memory management stochastic processes Information science

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Visualizing the Importance of Floor-Plan Image Features in Rent-Prediction Models

Visualizing the Importance of Floor-Plan Image Features in R...

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international Symposium on Soft computing and intelligent Systems (SCIS)

作者： Ryosuke Hattori Kazushi Okamoto Atsushi Shibata Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan Graduate School of Industrial Technology Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

This study proposes a rent-prediction model that allows users to understand which parts of a floor-plan image (FPI) significantly affect a rent prediction. Principal Component Analysis (PCA) and Bag of Features (BoF) are used to extract feature vectors from an FPI. The importance of each feature vector, derived from the FPI, is measured and visualized based on 100,000 rental properties sampled from the LIFULL HOME'S dataset. The experimental result suggests that the wall and orientation symbol drawn on an FPI contribute to the rent prediction for both PCA and BoF, although BoF provides a better understanding of which parts of an FPI significantly affect the rent prediction.

关键词： Principal component analysis Feature extraction Predictive models standards Visualization Image color analysis Training

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Comparison study between conventional machine learning and distributed multi-task learning models

Comparison study between conventional machine learning and d...

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Information technology (ACIT)

作者： Salam Hamdan Sufyan Almajali Moussa Ayyash Princess Sumaya University for Technology Amman Jordan Chicago IL USA

ISBN: (数字)9781728188553

ISBN: (纸本)9781728188560

Applying machine learning in IoT devices is a challenge due to various reasons, such as the tremendous amount of data generated from IoT, the limitation of IoT devices' resources, and the non-IID nature of IoT data. On the other hand, transferring the generated IoT data to the cloud to train machine learning models consumes a lot of Bandwidth. Applying the distributed learning aspect in IoT large-scale deployments solves such issues, by employing edge computing devices as local cloud models in each location. This solution enhances the network overhead and helps in obtaining general models. However, this comes at the expense of the accuracy of the generated models. This paper provides a comparison study between applying a conventional machine learning model with a distributed multi-task learning model and discusses the factors that affect the distributed multi-task learning model.

关键词： Cloud computing Data models Computational modeling Training Internet of Things Task analysis Edge computing

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Interactive Apparel Coordination Recommendation System Reflecting Situation and Preference

Interactive Apparel Coordination Recommendation System Refle...

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international Symposium on Soft computing and intelligent Systems (SCIS)

作者： Muneyuki Unehara Yui Hasegawa Koichi Yamada Izumi Suzuki Nagaoka University of Technology Japan Undergraduate School of Information and Management Systems Engineering Nagaoka University of Technology Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

This study proposes an apparel coordination recommendation system, which reflects the user's situation of wearing clothing and individual preference, based on the Interactive Evolutionary Computation. The proposed system is a practical method in three respects that are not found in previous studies. First, the images of the actual product were used so that the user could use in practice. Secondly, using the latest data from SNS, we generated the outfits that the system presents outfits based on the type and color of clothing that are actually paid attention. Thirdly, the subjective evaluation of the user is accumulated as an individual preference, and the outfit is presented by a simple procedure for daily use. From results of the experiments, it was confirmed that the proposed system was effective in clarifying and reconfirming the user's preference of outfits.

关键词： Clothing Image color analysis Databases Color User interfaces Multimedia Web sites Genetic algorithms

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Some Problems of Advancement of Modern Information technology in the Russian Engineering Education 21st

Some Problems of Advancement of Modern Information Technolog...

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21st international conference on Interactive Collaborative Learning (ICL) / 47th IGIP international conference on Engineering Pedagogy - Teaching and Learning in a Digital World

作者： Morshchilov, Maxim Petrova, Larisa Prikhodko, Vjatcheslav Abrakov, Sergey Moscow Automobile & Rd Construct State Tech Univ Moscow Russia

ISBN: (纸本)9783030119355;9783030119348

New technologies in engineering education are becoming more and more relevant every year. Under the term "new technologies" in the educational process we understand primarily and mainly various kinds of on-line courses, electronic educational resources and other types of information resources. The application of all of the above mentioned tools works to improve the process of students learning and helps to increase their professional relevance on the labor market. In the paper the features of information technology application for the purposes of engineering education in Russia are considered. The review has been conducted on the basis of analysis of the main factors affecting the use of information technology in engineering education. These factors run a whole gamut of the student personalities of the Z-generation, to computer literacy of the teaching staff and the structure of the educational process in engineering education. The factors considered are comprehensively analyzed and the ways of interaction between teachers and students are proposed and on their basis. Google Classroom usage is considered, as a variant of the system of interaction between teachers and students.

关键词： Engineering education Educational resources Online courses Z-generation Computer literacy

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An auto code generator for stencil on SW26010 21

An auto code generator for stencil on SW26010

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21st IEEE international conference on High Performance computing and Communications, 17th IEEE international conference on Smart City and 5th IEEE international conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Zhu, Xiaomin Zeng, Yunhui Wei, Yanjie Feng, Shengzhong Liu, Weiguo Balaji, Pavan Joint Engineering Research Center Health Big Data Intelligent Analysis Technology Center for High Performance Computing Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shandong Computer Science Center National SuperComputer Center in Jinan Jinan China Sclool of Software Shandong University Jinan China Argonne National Laboratory United States

ISBN: (纸本)9781728120584

stencil is a basic building block widely used in many HPC areas and applications. It generally dominates the time cost and is critical to the overall performance. Given that heterogeneous many-core is frequently adopted to build super computers, porting and optimizing stencil codes on modern accelerator-based architectures is important. Porting is non-trivial, and optimization is more difficult as it requires better understanding of the underlying architecture. As a result, auto tuning targeting on accelerators such as GPU becomes a hot research topic. In this paper, we focus on tuning stencil automatically on SW26010, which is a heterogeneous many-core CPU equipped in Sunway TaihuLight SuperComputer, and mainly work on 2D stencil variants code in ROMS (Regional Ocean Modeling System). The code generator can generate codes running on slave cores for 50+ different FORTRAN stencil-alike loops in ROMS in seconds, and optimization methods are integrated into the generator as well. The performance is better than the directive based method (OpenACC) and the hand-drafted code by a junior programmer, and it is comparable compared with the code written by a senior programmer with several years of programming experience. © 2019 IEEE.

关键词： Supercomputers

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Dynamic Algorithm for Building Future Networks Based on intelligent Core Network 23rd

Dynamic Algorithm for Building Future Networks Based on Inte...

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23rd international conference on distributed Computer and Communication Networks, DCCN 2020

作者： Khakimov, Abdukodir Muthanna, Ammar Elgendy, Ibrahim A. Samouylov, Konstantin Miklukho-Maklaya Street 6 Moscow117198 Russia The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Pr. Bolshevikov 22 St. Petersburg193232 Russia School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9783030664701

6G/IMT-2030 is designed to provide users with innovative speeds of terabit per second, which are proposed to be achieved using a number of advanced technologies, such as Mobile Edge computing (MEC), Internet of Things (IoT), millimeter wave (mmWave), new radio and software defined networking. It is necessary to solve several important aspects in order to satisfy Quality of Service (QoS), first of all, to ensure network coverage density even in sparsely populated areas. In this paper we proposed software defined network based mobile edge computing dynamic algorithm for improving network performance. In addition, this algorithm can help the service provided to adapt with a required load on the radio links. Furthermore, local content caching and Local Internet Breakout (LIB) can be utilized to reduce the transport network requirements. Finally, the proposed algorithm is analyzed using some use cases and we developed testbed to emulate operator infrastructure. © 2020, Springer Nature Switzerland AG.

关键词： Radio links

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