Simulations of Emergence of Proto-Japanese Particles Based on Emergent Computings
| Project/Area Number |
11837020
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Institution | Aichi University Junior College |
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Principal Investigator |
SUDA Junichi Aichi University, Junior College, Associate Professor, 助教授 (30310600)
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| Co-Investigator(Kenkyū-buntansha) |
YUKAWA Harutoshi Aichi University, Dept.of Economics, Associate Professor, 経済学部, 助教授 (40278221)
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| Project Period (FY) |
1999 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2000: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1999: ¥2,700,000 (Direct Cost: ¥2,700,000)
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| Keywords | Zipf's Law / Monte-Carlo Method / Linguistic Emergence in Genealogy and the Individual / Proto-Japanese Particles / Self-Organization / Emergent-symbolic Computing / Word Length / Artificial Words / 単語長 / 原日本語助詞 / 系進化 / 系発生 / 自然言語記号系 / 文法系 / 系統発生 / 個体発生 / 認知類型言語学 / Zipf則(ジップ法則) / 語彙獲得 |
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| Research Abstract |
1 Designing a model
(1) We evaluated some major computing algorisms. In conclusion, we found some Linguistic defects in those computing models plotted for language acquisition and language development.
(2) We have also come to the conclusion that we should not stick to Neural Network Models for our research.
2 Theoretical and Quantitative Heuristics for the new model
(3) We examined theories of Cognitive Linguistics for a dynamical model of the natural language system.
(4) We completed the translations of papers on the Zipf's Law both in German and in French.
(5) We mined some E.Long databases of the Tale of Genji to compute the Zipf's Law.
3 Simulations
(6) We examined sufficient databases of Old-Japanese in the Zipf's Law for heuristics of Proto-Japanese.
(7) We computed some parameters which passed the Zipf's Law examinations.
(8) We simulated how artificial words emerged using the Monte-Carlo Method.
(9) We computed the parameters to organize the Zipf's Law in each simulation above.
4 Data analysis and Discussions
(10) We have acquired some concrete heuristics on parameters to construct a new model on these simulations.
5 Revising the model
(11) We have completed plans and the concepts of a new model which plots the Zipf's Law as an evaluation-function using Emergent-Symbolic Computing based on the Monte-Carlo Method.
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Report
(3 results)
Research Products
(15 results)
