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Agent-Based Approaches in Economics and Social Complex Systems IX

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Cover of 'Agent-Based Approaches in Economics and Social Complex Systems IX'

Table of Contents

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    Book Overview
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    Chapter 1 Understanding Risks in Milk Supply Chain: An Agent-Based Conceptual Model
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    Chapter 2 People’s Willingness to Donate Blood: Agent-Based Approach
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    Chapter 3 An Agent-Based Simulation Approach for Government Intervention in Reducing High-Risk HPV
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    Chapter 4 Method for Getting Parameters of Agent-Based Modeling Using Bayesian Network: A Case of Medical Insurance Market
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    Chapter 5 Coping with Bullying in the Classroom Through Agent-Based Modeling
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    Chapter 6 How to Attract Customers to Your Website with Word-of-Mouth Communication in Social Media
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    Chapter 7 Land Use Decision-Making Strategy in Bandung: An Agent-Based Modeling Approach
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    Chapter 8 Agent-Based Simulations of Smallholder Decision-Making in Land Use Change/Cover (LUCC) Problem
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    Chapter 9 Understanding the Learning Processes of Traveller Behavioural Choices Using Agent-Based Approach: A Conceptual Framework
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    Chapter 10 Multi-agent Reinforcement Learning for Collaborative Transportation Management (CTM)
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    Chapter 11 Size Effects in Agent-Based Macroeconomic Models: An Initial Investigation
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    Chapter 12 The Effectiveness of Firm-Controlled Supporters to Pacify Online Firestorms: A Case-Based Simulation of the “Playmobil” Customize-It Incident
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    Chapter 13 Soft Systems Agent-Based Methodology: Multi-methods Approach Between Soft Systems Methodology and Agent-Based Modeling
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    Chapter 14 An Analysis of the Characteristics of a Proactive Exploration Behavior Model Based on Three-Dimensional Virtual Space Experiments
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    Chapter 15 Distributed Classifier System for Smart Home’s Machine Learning
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    Chapter 16 Delivering Value of Composting and Recycling in Household Waste Management System: An Agent-Based Modeling Approach
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1 tweeter
2 patents


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Agent-Based Approaches in Economics and Social Complex Systems IX
Published by
Springer, Singapore, May 2017
DOI 10.1007/978-981-10-3662-0
978-9-81-103661-3, 978-9-81-103662-0

Utomo Sarjono Putro, Manabu Ichikawa, Manahan Siallagan

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 56%
Student > Postgraduate 2 22%
Professor > Associate Professor 1 11%
Student > Master 1 11%
Readers by discipline Count As %
Economics, Econometrics and Finance 3 33%
Social Sciences 3 33%
Computer Science 1 11%
Agricultural and Biological Sciences 1 11%
Engineering 1 11%
Other 0 0%