| Co-Investigator(Kenkyū-buntansha) |
TAMAKI Hisashi Kobe Univ., Faculty of Engineering, Associate Professor, 工学部, 助教授 (10227267)
NAGSAKA Ichiro Kobe Univ., Faculty of Letters, Associate Professor, 文学部, 助教授 (10314501)
KIKUCHI Makoto Kobe Univ., Faculty of Engineering, Associate Professor, 工学部, 助教授 (60273801)
MURAO Hajime Kobe Univ., Faculty of Cross-Cultural Studies, Associate Professor, 国際文化学部, 助教授 (70273761)
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| Budget Amount *help |
¥12,000,000 (Direct Cost: ¥12,000,000)
Fiscal Year 2003: ¥4,600,000 (Direct Cost: ¥4,600,000)
Fiscal Year 2002: ¥7,400,000 (Direct Cost: ¥7,400,000)
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| Research Abstract |
The project aimed at clarifying and also interpreting the creativity and the comprehensive ability of human which were revealed in the process of designing artifacts, and included the following sub-themes : (1) analysis of the mathematical structure of "interactive information fields" which describe the informational flow between human and computers, (2) emergent design theories based on learning (application of reinforcement learning to such problems that the information on an environment is incomplete), and (3) emergent design theories based on interaction (application of interactive evolutionary computation to such problems that the specification is also incomplete).
In the course of the sub-theme (1), first by taking classifier systems for the example, their mathematical modeling based on the situation theory and the channel theory was investigated. As for the abstract design theory, by focusing on abduction, the mathematical formulation of non-deductive reasoning was given, which clarified the relationship among induction, abduction and system design.
In the sub-theme (2), the frameworks based on reinforcement learning and genetics-based machine learning were reconstructed as the mechanism of acquiring the internal model of an environment as well as seeking for a solution. Through some computational experiments for the problems of real-time scheduling, generating a walking pattern of biped robots, navigating a robot, and so on, the effectiveness of the frameworks was examined.
Furthermore, in the sub-theme (3), methods of interactive evolutionary computation, which utilized the ambiguous decisions of human, were mainly considered. The computational models of a co-evolutionary genetic algorithm as well as a genetic algorithm with sexual selection were investigated, and the potential of these models was confirmed through computational experiments.
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