Takao Terano

Agent-Based In-Store Simulator for Analyzing Customer Behaviors in a Super-Market

This paper presents an agent-based simulator to investigating customer walking flows and purchasing behaviors in a super market. So far, such investigations have cost very much to examine in real situations. The simulator enables us to carry out virtual experiments through changing various parameters of retail businesses and store operations. For this purpose, first we observe an actual retail store and analyze sales data. Then we develop the simulation model: Agent-Based In-Store Simulator (ABISS). Intensive experiments have revealed that the flow of customers, which is related to the sales, depends on the design of a store and that the places of in-store advertisement and recommendation system vary their sales.

We need multiple solutions for electric equipments configuration in a power plant - applying Bayesian optimization algorithm with Tabu search

This paper addresses electric equipments configuration problems in a power plant. The problems are large-scale nonlinear combinatorial optimization problems with various constraints. In this paper, we apply Bayesian optimization algorithm with Tabu search (Tabu-BOA) to the problems. From intensive experiments, the proposed method has shown the effectiveness to practical problems.

HISTORICAL SIMULATION: A STUDY OF CIVIL SERVICE EXAMINATIONS, THE FAMILY LINE AND CULTURAL CAPITAL IN CHINA

In this study, we investigate what would happen in a Chinese historical family line. We have analyzed a particular family line which had a great many candidates who passed the very tough examinations for Chinese government officials over 500 years. First, we studied the genealogical records Zokufu in China. Second, based on the study, we implemented an agent-based model with the family line network as an adjacency matrix, and the personal profile data as an attribution matrix. Third, using the inverse simulation technique, we optimized the agent-based model in order to fit the simulation profiles to the real profile data. From the intensive experiments, we have found that both grandfather and mother have a profound impact within a family in (1) transmitting cultural capital to the children, and (2) maintaining the norm system of the family. We conclude that advanced agent-based models are able to contribute to the discovery of new knowledge in the fields of historical science.

Identification of Voting with Individual’s Feet Through Agent-Based Modeling

This paper describes an agent-based simulation model to analyze migration behaviors of individual in several political regions. The model was originally discussed by Tiebout in 1956 as “Voting with Feet,” however, the validity of the model has not been examined very carefully. In the proposed agent simulation model, plural political decisions in each region are made by the corresponding regional government, and the inhabitants will vote the decisions based on their preferences. Both governments and individuals are modeled as decision making agents. The intensive simulation studies have revealed the emergence of decision groups and how the decisions have been made.

Analyzing the ENRON Communication Network Using Agent-Based Simulation

Agent-based modeling, simulation, and network analysis approaches are one of the emergent techniques among soft computing literature. This paper presents an agent-based model for analyzing the characteristics of peer-to-peer human communication networks. We focus on the process of the collapse of Enron Corporation, which is an interesting topic among the business management domain. The Enron email dataset is available for the analysis. Our approach consists of the four steps: First, macro-level characteristics of the Enron email dataset is analyzed from the viewpoints of social network theory: (i) the degrees of the communication networks and contents information, and (ii) the changes of network structures among the major events. Second, for the micro-level analysis, an agent-based simulator is implemented using the Enron email dataset. Third, both micro- and macro- level characteristics are calculated on the simulator to ground the model to the dataset. Finally, a different artificial society from the Enron email dataset is developed the simulator and we compare its characteristics of communication patterns with the result of the ones in the agent-based simulation with the Enron email dataset. The investigation suggests that the agent-based model is beneficial to uncover the characteristics of implicit communication mechanisms of the firm.

QC chart mining: extracting systematic error patterns from quality control charts

This paper presents a novel method; QC Chart Mining, which extracts systematic error patterns from quality control charts in order to manage clinical test data at a medical laboratory. In this paper we describe the basic principle of a time series decomposition mechanism for QC Chart Mining. QC Chart Mining is used to recognize quality problems such as long-term trends and/or daily cyclic variations in analytical processes of clinical tests, then to improve the quality level over clinical laboratory medicine. Intensive experiments from both actual quality-control data and artificial data have revealed the validity of the proposed method. Our results have shown that the proposed method is useful and effective for quality management in a medical laboratory.

Yutori Is Considered Harmful: Agent-Based Analysis for Education Policy in Japan

This chapter describes an agent-based simulation of the influence of education policy upon stratified students’ academic abilities. We have proposed that the academic achievement gap in the social stratum is not caused by academic ability or investment in education, but by the action rules for task achievement, that is, by the motivation to learn. It suggests that education policy should aim at cultivating students’ motivation to learn.

Agent-based approach to economic and social complex systems

The special issue of New Generation Computing consists of one survey paper and six contributed papers, which contribute a new emergent field of computer sciences: agent-based modeling to economic and social complex systems. The word agent has various meanings in the computer sciences. In this issue, the word means small software agents for simulation studies with internal states and decision models with which they are able to interact each other in a given static and/or dynamic environment in order to uncover complex economic and social phenomena. Recent software technology has matured to attack complex economic and social problems which require collective information processing with a large collection of autonomous and heterogeneous agents. Researchers on the field have increased the awareness of the members of the community concerning the following three basic issues:

HHM-Based risk management for business gaming

Business Gaming is a methodology for examining new business models in e-business field. This paper aims at improving the methodology to handle risk factors in the model. We utilize Hierarchical Holographic Modeling method (HHM method) for the risk assessment. In this paper, we develop a new risk assessment process on the IT-System Security field within the business gaming environment. We model knowledge related to risks by HHM method. The results suggest the effectiveness of applying the models into the Business Game environment.

Human-agent participation via software agents for business modeling

This paper proposes a novel approach to business simulator development in marketing domains. We are conducting an educational course, which consists of (i) a simple gaming experiment among human students and multiple software agents, (ii) home-made simulator implementation by the students themselves using a business model description language (BMDL), Agent Rules In Ruby Language, and a business model development system (BMDS). Our course is unique in the sense that, through the business simulation, we aim to develop students skills (1) to implement their own specific models of business firms, (2) to develop an information system for the firms, (3) to grasp decision making procedures by the players, and (4) to understand business processes among companies. This paper describes the background and motivation, basic principles, the architecture and implementation, and experiments.