Agents and Multi-Agent Systems: Technologies and Applications 2020

14th KES International Conference, KES-AMSTA 2020, June 2020 Proceedings
 
 
Springer (Verlag)
  • 1. Auflage
  • |
  • erschienen am 20. Mai 2020
  • |
  • XVI, 368 Seiten
 
E-Book | PDF mit Adobe-DRM | Systemvoraussetzungen
E-Book | PDF mit Wasserzeichen-DRM | Systemvoraussetzungen
978-981-15-5764-4 (ISBN)
 

The book highlights new trends and challenges in research on agents and the new digital and knowledge economy. It includes papers on business process management, agent-based modeling and simulation and anthropic-oriented computing that were originally presented at the 14th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2020), being held as a Virtual Conference in June 17-19, 2020. The respective papers cover topics such as software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems and nature inspired manufacturing, all of which contribute to the modern digital economy.

1st ed. 2020
  • Englisch
  • Singapore
  • |
  • Singapur
47 schwarz-weiße und 93 farbige Abbildungen, Bibliographie
  • 12,84 MB
978-981-15-5764-4 (9789811557644)
weitere Ausgaben werden ermittelt

Gordan Jezic is a Professor at the University of Zagreb, Croatia. His research interest includes telecommunication networks and services focusing particularly on parallel and distributed systems, machine-to-machine (M2M) and Internet of Things (IoT), communication networks and protocols, mobile software agents and multi-agent systems. He actively participates in numerous international conferences as a paper author, speaker, member of organizing and program committees or reviewer. He co-authored over 100 scientific and professional papers, book chapters and articles in journals and conference proceedings.

Yun-Heh Jessica Chen-Burger is an Assistant Professor, Computer Science, Heriot-Watt University. She was Research Fellow, Informatics, University of Edinburgh. Her research interests include enterprise modeling, process modeling, execution and mining technologies and how they may interact with agent technologies to solve complex real-world problems. She is committee member of several international conferences, journals and chair of conference and conference sessions. She is PI to several research and commercial projects.

Mario Kusek is Professor at the University of Zagreb, Croatia. He holds Ph.D. (2005) in electrical engineering, from the University of Zagreb. He is currently a lecturer of 9 courses and has supervised over 130 students at B.Sc., M.Sc. and Ph.D. studies. He participated in numerous projects local and internationals. He has co-authored over 80 papers in journals, conferences and books in the area of distributed systems, multi-agent systems, self-organized systems and machine-to-machine (M2M) communications. Prof. KuSek is a member of IEEE, KES International and the European Telecommunications Standards Institute (ETSI). He serves as a program co-chair on two international conferences.

Roman sperka is an Associate Professor and Head of Department of Business Economics and Management at Silesian University in Opava, School of Business Administration in Karvina, Czech Republic. He holds Ph.D. title in "Business economics and management" and Dr title in "Applied informatics" since 2013. He has been participating as a head researcher or research team member in several projects funded by Silesian University Grant System or EU funds. His field of expertise is business process management, process mining, implementation and deployment of information systems and software frameworks; the use of agent-based technology in social sciences; modeling and simulation in economic systems and financial markets.

Dr. Robert Howlett is the Executive Chair of KES International, a non-profit organization that facilitates knowledge transfer and the dissemination of research results in areas including intelligent systems, sustainability and knowledge transfer. He is a Visiting Professor at Bournemouth University in the UK. His technical expertise is in the use of intelligent systems to solve industrial problems. He has been successful in applying artificial intelligence, machine learning and related technologies to sustainability and renewable energy systems; condition monitoring, diagnostic tools and systems and automotive electronics and engine management systems. His current research work is focused on the use of smart microgrids to achieve reduced energy costs and lower carbon emissions in areas such as housing and protected horticulture.

Dr. Lakhmi C. Jain, Ph.D., M.E., B.E. (Hons), Fellow (Engineers Australia) is with the University of Technology Sydney, Australia, and Liverpool Hope University, UK. Professor Jain serves the KES International for providing a professional community the opportunities for publications, knowledge exchange, cooperation and teaming. Involving around 5,000 researchers drawn from universities and companies worldwide, KES facilitates international cooperation and generates synergy in teaching and research. KES regularly provides networking opportunities for professional community through one of the largest conferences of its kind in the area of KES.

  • Intro
  • KES-AMSTA 2020 Conference Organization
  • Honorary Chairs
  • Conference Co-Chairs
  • Executive Chair
  • Program Co-Chairs
  • Publicity Chair
  • International Program Committee
  • Invited Session Chairs
  • Preface
  • Contents
  • About the Editors
  • Software Agents in Smart Environment
  • Revitalising and Validating the Novel Approach of xAOSF Framework Under Industry 4.0 in Comparison with Linear SC
  • 1 Introduction
  • 2 Test Scenario and AOSF
  • 3 Dataset and Test Cases
  • 4 Results and Discussion
  • 5 Conclusion and Future Work
  • References
  • Natural Language Agents in a Smart Environment
  • 1 Introduction
  • 2 Spoken Interaction in Smart Environments
  • 3 Language Agents in a Smart Environment
  • 4 Generating Textual Notifications in the Croatian Language
  • 5 Synthesizing Spoken Notifications in the Croatian Language
  • 6 Case Study-Spoken Notifications in a Smart Home
  • 7 Conclusion
  • References
  • Potentials of Digital Business Models for the European Agriculture Sector
  • 1 Introduction
  • 2 Digitization and Digital Business Models in Agriculture
  • 3 Research Design and Method
  • 3.1 Research Methods and Data Collection
  • 4 Empirical Results
  • 5 Discussion and Limitations
  • 6 Conclusion
  • References
  • Agent-Based Approach for User-Centric Smart Environments
  • 1 Introduction
  • 2 Related Work
  • 3 Agent-Based Model
  • 3.1 Centralized Approach
  • 3.2 Agent-Based Approach
  • 4 Use Case: Smart Lighting
  • 4.1 Agent-Based
  • 5 Conclusion and Future Work
  • References
  • Providing Efficient Redundancy to an Evacuation Support System Using Remote Procedure Calls
  • 1 Introduction
  • 2 Background
  • 2.1 Evacuation Support System
  • 2.2 Redundant Arrays of Inexpensive Disks
  • 2.3 Remote Procedure Call
  • 3 System Overview
  • 3.1 Monitoring
  • 3.2 Recovery
  • 4 Experiments
  • 5 Conclusion and Future Directions
  • References
  • Process Model for Accessible Website User Evaluation
  • 1 Introduction
  • 2 Process of Accessible Website Prototype Evaluation
  • 2.1 Functional Testing of Accessible Website Prototype
  • 2.2 Evaluation of Accessible Website Prototype User Experience
  • 3 Results of Conducted Surveys for UXE of Web Prototype
  • 3.1 Results from First Conducted Survey for UXE
  • 3.2 Results from Second Conducted Survey for UXE
  • 4 Conclusion
  • References
  • Intelligent Agents and Cloud Computing
  • A Comparative Study of Trust and Reputation Models in Mobile Agent Systems
  • 1 Introduction
  • 2 Need of Trust Evaluation in Mobile Agent Systems
  • 3 Trust and Reputation Background
  • 3.1 Trust and Reputation Definition
  • 3.2 Trust and Reputation Model Steps
  • 3.3 Trust and Reputation Model Dimensions
  • 4 Comparing Trust Models for Mobile Agent Systems
  • 5 New Dimensions
  • 6 Application Scenario
  • 7 New Trust Model Flowchart
  • 8 Conclusion
  • References
  • Agent-Based Control of Service Scheduling Within the Fog Environment
  • 1 Introduction
  • 2 Related Work
  • 3 Enabling Service Scheduling Technologies
  • 4 Agent-Based Approach for Service Migration Control in Fog Environment
  • 4.1 Role Distribution Among the Involved Entities
  • 4.2 Simulation Scenario
  • 4.3 Simulation Result
  • 5 Conclusion
  • References
  • On the Conception of a Multi-agent Analysis and Optimization Tool for Mechanical Engineering Parts
  • 1 Introduction
  • 2 Theoretical Background and Related Work
  • 3 Conceptualizing an Agent-Based Analysis and Optimization Tool for Mechanical Engineering Parts
  • 3.1 Evaluation 1: Design Review
  • 3.2 Design
  • 3.3 Proof-of-Concept
  • 4 Test Case
  • 5 Discussion and Conclusion
  • References
  • Predicting Dependency of Approval Rating Change from Twitter Activity and Sentiment Analysis
  • 1 Introduction
  • 2 Related Work
  • 3 Data Set Analysis
  • 4 Methodology and Results
  • 5 Conclusion
  • References
  • Protected Control System with RSA Encryption
  • 1 Introduction
  • 2 Problem Statement
  • 2.1 Control System Model
  • 2.2 False Data Injection
  • 3 RSA Encryption
  • 3.1 Algorithm Description
  • 3.2 False Data Injection Detection
  • 4 Implementation
  • 4.1 Data Conversion
  • 4.2 Analysis of Discrete Controller Implementation on Control Quality
  • 5 Numerical Example
  • 6 Conclusion
  • References
  • Artificial Intelligent Agent for Energy Savings in Cloud Computing Environment: Implementation and Performance Evaluation
  • 1 Introduction
  • 2 Related Work
  • 3 IAA-EATSVM Architecture
  • 4 Performance Analysis
  • 4.1 Experimental Environment
  • 4.2 Experiments
  • 4.3 Experimental Results Analysis
  • 5 Conclusion
  • References
  • Agent-Based Modeling and Simulation and Business Process Management
  • Design of Technology for Prediction and Control System Based on Artificial Immune Systems and the Multi-agent Platform JADE
  • 1 Introduction
  • 2 Statement of the Problem
  • 3 Solution Methods
  • 4 Intelligent System of Prediction and Control of Complex Objects on the Basis of Multi-agent Platform JADE
  • 5 Simulation Results
  • 6 Conclusion
  • References
  • A Multi-agent Framework for Visitor Tracking in Open Cultural Places
  • 1 Introduction
  • 2 Review of Related Works
  • 3 Multi-agent System (MAS)
  • 4 The Proposed System
  • 4.1 Overview
  • 4.2 The Employed Agents
  • 4.3 Methodology
  • 5 Simulation Results
  • 5.1 Simulation Setup
  • 5.2 The Impact of Similarity Threshold
  • 6 Conclusions and Future Work
  • References
  • Toward Modeling Based on Agents that Support in Increasing the Competitiveness of the Professional of the Degree in Computer Science
  • 1 Introduction
  • 1.1 Objective
  • 1.2 Justification
  • 1.3 Related Cases
  • 2 Referential Framework
  • 2.1 Complex Systems
  • 2.2 Agent-Based Model
  • 2.3 Higher Education, Skills, and Labor Sector
  • 3 Methodology
  • 4 Modeling Proposal
  • 5 Conclusions
  • 6 Future Woks
  • References
  • Human Tracking in Cultural Places Using Multi-agent Systems and Face Recognition
  • 1 Introduction
  • 2 Related Works
  • 3 Proposed System
  • 3.1 Complexity of System
  • 4 Simulation of Experiment
  • 5 Conclusion and Future Work
  • References
  • A Conceptual Framework for Agent-Based Modeling of Human Behavior in Spatial Design
  • 1 Introduction
  • 2 Relevant Background
  • 3 An Agent-Based Model of Human Spatial Behavior
  • 3.1 Initial Elements
  • 3.2 Modeling Agent's Behavior
  • 4 Conclusions
  • References
  • Real-Time Autonomous Taxi Service: An Agent-Based Simulation
  • 1 Introduction
  • 2 Multi-agent AT Dispatch System
  • 3 Dispatching Method for Real Time AT Service
  • 4 AT Simulation
  • 5 Results
  • 6 Conclusion
  • References
  • Modelling Timings of the Company's Response to Specific Customer Requirements
  • 1 Introduction
  • 2 Mathematical Model
  • 3 Conclusions
  • References
  • Importance of Process Flow and Logic Criteria for RPA Implementation
  • 1 Introduction
  • 2 Criteria for Robotic Process Automation
  • 3 Methodology
  • 4 Results
  • 5 Conclusions
  • References
  • Agents and Multi-agents Systems Applied to Well-Being and Health
  • Multiagent System as Support for the Diagnosis of Language Impairments Using BCI-Neurofeedback: Preliminary Study
  • 1 Introduction
  • 2 Related Work
  • 3 Methods and Materials
  • 3.1 Multi-agent Model
  • 3.2 Agent Based on Mobile Application
  • 3.3 EEG Data Acquisition Agent
  • 3.4 EEG Analysis and Treatment Agent
  • 3.5 Clasification Agent
  • 4 Conclusion
  • References
  • Multi-agent System for Therapy in Children with the Autistic Spectrum Disorder (ASD), Utilizing Smart Vision Techniques-SMA-TEAVI
  • 1 Introduction
  • 2 What Is Autism?
  • 2.1 Primary Emotions
  • 2.2 Theory of Mind (ToM)
  • 2.3 Multi-agent Systems (MAS)
  • 2.4 Artificial Vision
  • 2.5 Facial Recognition
  • 3 Proposal
  • 3.1 Proposal Design
  • 4 Conclusions
  • References
  • Multiagent Monitoring System for Oxygen Saturation and Heart Rate
  • 1 Introduction
  • 2 Intelligent Agents
  • 3 Internet of Health Things
  • 4 Methodology
  • 5 Results and Discussions
  • References
  • Multi-agent System for Obtaining Parameters in Concussions-MAS-OPC: An Integral Approach
  • 1 Introduction
  • 2 Concepts
  • 2.1 What Is a Brain Concussion?
  • 2.2 What Are the Symptoms?
  • 2.3 What to Do in Case of Concussion?
  • 2.4 Brain Injury
  • 2.5 Physical Science
  • 2.6 Magnitudes
  • 2.7 Mathematical Representation
  • 2.8 Deep Learning
  • 2.9 Multi-agent System (MAS)
  • 2.10 Chronic Traumatic Encephalopathy (CTE)
  • 2.11 CTE in Football
  • 3 Justification
  • 4 Proposal
  • 4.1 Proposal Design
  • 5 Conclusions
  • References
  • Data Analysis of Sensors in Smart Homes for Applications Healthcare in Elderly People
  • 1 Introduction
  • 2 Background
  • 3 Methodology
  • 4 Development and Results
  • 5 Conclusion and Future Work
  • References
  • A Genetic Algorithm-Oriented Model of Agent Persuasion for Multi-agent System Negotiation
  • 1 Introduction
  • 2 Persuasion Model
  • 2.1 Conceptual Model
  • 2.2 Information Model
  • 2.3 Persuasion Model Application Characteristics
  • 3 Experimental Design
  • 4 Results
  • 5 Conclusion and Future Work
  • References
  • Business Informatics
  • Impacts of the Implementation of the General Data Protection Regulations (GDPR) in SME Business Models-An Empirical Study with a Quantitative Design
  • 1 Introduction
  • 2 Research Design
  • 2.1 Qualitative Research
  • 2.2 Quantitative Design
  • 3 Empirical Results
  • 4 Discussion and Limitations
  • 5 Conclusion
  • References
  • A Study on the Influence of Advances in Communication Technology on the Intentions of Urban Park Users
  • 1 Introduction
  • 2 Background
  • 2.1 Development of Communication Technology in Japan
  • 2.2 Urban Park in Japan
  • 3 Data Configuration and Experimental Method
  • 4 Experimental Result
  • 5 Concluding Remarks and Future Work
  • References
  • Construction of News Article Evaluation System Using Language Generation Model
  • 1 Introduction
  • 2 Data
  • 2.1 Market Data
  • 2.2 News Data
  • 3 News Article Evaluation System Using Language Generation Model
  • 3.1 Overview
  • 3.2 Labeling Based on Stock Price Fluctuations
  • 3.3 News Articles Generation
  • 3.4 Vectorization of News Articles
  • 3.5 Classification Through the LSTM Model
  • 4 Results
  • 4.1 Labeling Based on Stock Price Fluctuations
  • 4.2 Generating News Using GPT-2
  • 4.3 Results of Model Accuracy
  • 5 Summary
  • References
  • Constructing a Valuation System Through Patent Document Analysis
  • 1 Introduction
  • 2 Related Work
  • 3 Data
  • 4 Algorithm
  • 5 Result
  • 6 Conclusion
  • References
  • Modeling of Bicycle Sharing Operating System with Dynamic Pricing by Agent Reinforcement Learning
  • 1 Introduction
  • 2 Related Work
  • 2.1 Main Factors in Commuters' Choice of Traffic Behavior
  • 2.2 Behavioral Change by Incentive
  • 2.3 Agent Simulation Using Reinforcement Learning
  • 3 Simulation Model
  • 3.1 Behavior Selection Model
  • 3.2 Environment
  • 3.3 Demand Curve
  • 4 Experiments
  • 4.1 Simulation Scenario
  • 4.2 Experimental Results
  • 4.3 Discussion
  • 5 Conclusion
  • References
  • Omni-Channel Challenges Facing Small- and Medium-Sized Enterprises: Balancing Between B2B and B2C
  • 1 Introduction
  • 2 Related Work
  • 2.1 Stages to Achieve Omni-Channel Sales Strategy
  • 2.2 Consumer Decision-Making in EC
  • 3 Research Method: Using a Case of Health Food
  • 4 Concept Development of a Health Food Product
  • 4.1 Customer Survey
  • 4.2 Building a Marketing Strategy
  • 5 Sales Simulation
  • 5.1 Objectives and Core Settings
  • 5.2 Simulation Results
  • 6 Conclusions
  • References
  • A Formal, Descriptive Model for the Business Case of Managerial Decision-Making
  • 1 Introduction
  • 2 Methodologies
  • 2.1 Three Major Components
  • 2.2 Composing the Decision Diagram
  • 2.3 Properties of the Decision Diagram
  • 2.4 Set-Theoretic Description of MDDM
  • 3 Application to Actual Business Cases
  • 4 Application to Organizational ABS Logs as Virtual Business Cases
  • 5 Summary and Remarks
  • References
  • Author Index

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