Junji Nishino

A high performance IDS processing unit for a new fuzzy-based modeling

This paper presents a hardware unit for modeling systems using the active learning method (ALM). The ALM, a new methodology of soft computing, has processing units called IDSs, which are tasked with extracting useful information from a system subject to modeling. In realizing the ALM in hardware, it is desirable in terms of processing nature, performance, and scalability to utilize dedicated hardware for IDS. A developed high performance IDS processing unit enables ALM-based modeling systems to increase real-time capabilities. The hardware implementation of IDS and performance test results of the hardware are reported, and a consideration of the redundancy of IDS processing units is described.

Acquisition of control knowledge of nonholonomic system by Active Learning Method

In this paper, we propose the Active Learning Method, the method to acquire the control knowledge actively by the method of trial and error. In this method, the input-output information is collected for the control object by the method of trial and error, and the controller is constructed based on the information. In the Active Learning Method, the output is decided actively and the action result is evaluated, and the data with high evaluation are modeled. This modeled pattern information becomes the behavior policy optimized based on the evaluation. For this modeling, the method called Ink Drop Spread method (IDS) is used. In this system, the object system is modeled functionally from the data by the fuzzy-like processing. By using the model of bar gymnast, the learning simulation is done for the behavior policy, and we examine the validity of this method.

A hardware design for a new learning system based on fuzzy concepts

This paper presents a hardware system that implements the active learning method (ALM), a methodology of soft computing. ALM has processing engines called IDS, which are tasked with extracting useful information from a system subject to modeling. In realizing ALM in hardware, it will be desirable in terms of processing nature, performance, and scalability to utilize dedicated hardware for IDS. This paper primarily describes the actual hardware design of an IDS module, and shows the findings of tests of an ALM hardware system that implemented this module.

Fuzzy linguistic facial caricature drawing system

Considers a realization of a process drawing facial caricatures and exaggerating them using the concept of fuzzy information granulation. Face space is introduced, for the facial caricature drawn in computer graphics. The linguistic terms which indicate features of ones face are given as a fuzzy set by means of the concept of computing with words. Exaggerated knowledge is realized as rules on linguistic labels. Also simulation examples of facial caricature drawing and exaggerating are shown.

Investigation of the effects of nonverbal information on werewolf

Werewolf is one of the popular communication games all over the world. It treats ambiguity of human discussion including the utterances, gestures and facial expressions in a broad sense. In this research, we pay attention to this imperfect information game werewolf. The purpose of the research is to develop an intelligent agent “AI werewolf” which is enabled to naturally play werewolf with human. This paper aims to investigate how behavior contribute to victory of own-side players by using machine learning as a first step. As the results of investigation and analysis of the playing movie, we found that nonverbal information in the game of werewolf has importance to winning or losing the game.

Refining fuzzy control rules for the inverted double pendulum system based on a transformation-type genetic algorithm

We have been studying fuzzy control of the inverted double pendulum in computer simulations. We can control the inverted double pendulum by fuzzy control rules acquired by trial and error. In this research, we attempted to acquire fuzzy control knowledge for the double pendulum automatically by using a genetic algorithm (GA). In order to adjust the rules of attitude and position control of the double pendulum by the GA, we regarded rule acquisition as a multiobjective optimization problem and formulated hierarchical control knowledge. This paper proposes a new method of treating hierarchical control knowledge by expanding the GA with a local improvement mechanism. This method, based on genetic transformation in microorganisms, allows us to acquire better fuzzy control knowledge of the double pendulum.

Konohen fuzzy: A sample points based computational model for multi-dimensional fuzzy set

In this paper, Multi-dimensional fuzzy set calculation model is introduced, and the method is called Konohen fuzzy. For some actual purposes, formal expression functional model for multi-dimensional solution space can not be obtained so easily. We propose the SPF : sample points based fuzzy set definition method to descrive multi-dimensional fuzzy set which is used to model problems on high-dimensional solution spaces. Konohen fuzzy handles more free styled fuzzy set shapes in multi-dimensional spaces than previous methods. The SPF is consist of a set of random finite sample points and a set of their membership values. Membership values of arbitrary points are obtained using interpolation, and this method makes it possible to handle complex and complicated systems in simple way that is an original goal of fuzzy logic. A numerical example results show that calculation error between SPF and overall interpolation is very small.

Digital Subtraction Angiogram Registration Method with Local Distortion Vectors to Decrease Motion Artifact

We have been investigating registration methods for improving digital subtraction angiography (DSA) images to extract blood vessels by reducing artifacts due to body motion, such as rotation, contraction, and dilation. In this paper, we propose a new and simple DSA registration algorithm with local distortion vectors to reduce artifacts. According to the results, the proposed method works well for vascular system around the nasal cavity and the orbit of the head and neck DSA images, which cannot be observed clearly by conventional methods. Additionally, we have applied the proposed method to abdominal and leg DSA images.

Open Zeng: An Open Style Distributed Semi-cooperative Team Development Project from Japan

The team Open Zeng is a quite interesting and unique project to study subjects on heterogeneous cooperative teamwork behavior. Twelve players from seven different university and institutions were gatherd and played soccer well against ordinary teams. We introduced the Evolutionary development model. The project provides a distributed heterogeneous team development using WWW and eMail.

Zeng99: RoboCup Simulation Team with Hierarchical Fuzzy Intelligent Control and Cooperative Development

This paper discusses the design of the team Zeng99. The goal of team Zeng99 is to show a performance of Hierarchical Fuzzy Intelligent Control system in the field of multi agent problems. It worked well at RoboCup99 competition, even with little error in an invoking clients. It also allow independent/cooperative development client by client.