[in Japanese]

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[in Japanese]

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Generative Topographic Mapping (GTM) is a data visualization technique that uses a nonlinear topographically preserving mapping from latent to data space. The conventional GTM model can be interpreted as a probabilistic model with Gaussian process prior, and the choice of covariance function in the Gaussian process prior has an important effect on its properties. However the conventional GTM approach uses a covariance function with a constant length-scale for whole latent space, and therefore fails to adapt to variable smoothness of the nonlinear topographically preserving mapping. In this paper, we propose the GTM model which can control the smoothness in local areas of the latent space individually.

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We assume that SOM is adequate as a language acquisition model of the native phonetic system. However, many studies don't consider the quantitative features (the appearance frequency and the number of frames of each phoneme) of the input data. Our model is designed to learn values of the acoustic characteristic of a natural continuous speech and to estimate the number and boundaries of the vowel categories without using explicit instructions. In the simulation trial, we investigate the relationship between the quantity of learning and the accuracy for the vowels in a single Japanese speaker's natural speech. As a result, it is found that the recognition accuracy rate (of our model) are 5% (/u/)-92% (/s/).

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Based on check-up data of Ningen-Dock, a support tool for the health-care-service Dr. Ningen-Dock has been constructed using the SOM. The ability to visualize with our method the positional relations between the metabolic syndrome (MS) indicators and the health conditions further adds to its usability as a health guidance tool. Besides, other lifestyle related diseases or falling functions such as liver, diabetes, kidney, blood-general and inflamed-immunity will be judged through the same SOM method. Finally, the individual total judging score with the graph is systematically given which yields useful health care and guidance.

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Recently, complex vector truth value and its optical representation have been studied.
In this paper, we propose complex vector fuzzy logic, which can treat fuzzy truth values of Type-2 easily. Furthermore, this paper proposes realization of logical gates for operations of complex vector truth value from optical engineering's point of view. Logical gates proposed in the paper enable us to realize reversible computing of fuzzy truth values.

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In this paper, we focus on models dealing with interactions between players playing a coordination game in networks. For a detailed examination of equilibrium selection, we employ agent-based simulation analysis, and consider the influence of network structures on interaction of players in networks. In a newly developed simulation system, agents repeatedly play the games, and they can adaptively select strategies through this learning process. Decision making and learning mechanism of agents are implemented by using a neural network and the genetic algorithm. As a result of the simulations where the values of the parameters of the networks and the coordination games are varyingly arranged, we find that the risk-dominant strategy in a random network is superiority over the payoff-dominant one, and the payoff-dominant one in a local network is superiority over the risk-dominant one, compared to the other networks. Moreover, it is also found that depending on the situation, the behavior of agents in a small-world network exhibits properties similar to that of agents in a random network or in a local one.

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This paper discusses partner robot interaction based on frankl's psychology to prompt a person act voluntarily. Recently, elderly people who live alone in a room is increased. But, it is hoped that the elderly people keep good health. To keep good health for elderly people, a human should act voluntarily. To discuss the meaning of life, Frankl's psychology insists that the meaning of life is required from external stimuli. Frankl's psychology defines the 3 fields of value which are provided from external stimuli, and insists that the meaning of life and to be done will be found according to the value getting. Therefore, it is expected that a person would act voluntarily if a person find the meaning and value of life from external stimuli through interacting with a partner robot. In this research, we propose the robot interaction method based on frankl's psychology. And we propose the external value inference method based on the fields of value which estimates a situation from environmental change. Through human-robot interaction experiment based on frankl's psychology, we verify that a human acts voluntarily by finding the external value. Moreover, we discuss the possibility of interaction method based on frankl's psychology.

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