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Development of a system to predict further ahead about the effects of the law

Research Project

Project/Area Number 19K22899
Research Category

Grant-in-Aid for Challenging Research (Exploratory)

Allocation TypeMulti-year Fund
Review Section Medium-sized Section 62:Applied informatics and related fields
Research InstitutionNiigata Institute of Technology

Principal Investigator

Nakamura Makoto  新潟工科大学, 工学部, 教授 (50377438)

Co-Investigator(Kenkyū-buntansha) 的場 隆一  富山高等専門学校, その他部局等, 准教授 (30592323)
萩原 信吾  富山高等専門学校, その他部局等, 准教授 (50635224)
Project Period (FY) 2019-06-28 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2021: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2020: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2019: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Keywords労働契約法 / マルチエージェント / シミュレーション / 雇い止め / Q学習 / 改正労働契約法 / 強化学習 / 労働市場 / エージェント / 法的推論
Outline of Research at the Start

本研究の目的は,法律制定後から人の動向を予測するモデルを提案し,数年後に与える社会的,経済的な効果を予測することで政策決定に必要な新たな判断材料を提供することである.
本研究においては,法的推論を元に自律的に行動するエージェントを提案し,シミュレーションによる検証を行う.すなわち,関連する複数の法令から論理式を作成し,法的推論に必要なモデル化を行う.研究対象には,雇い止めのような社会的影響があった過去の事例をテーマに取り上げる.マルチエージェントシステムによるシミュレーションの結果,経済格差の広がりを観察するなど,法律施行後の社会を予測することなどが期待できる.

Outline of Final Research Achievements

The purpose of this study is to propose a model that predicts two moves ahead after a law is enacted, and to predict the social and economic effects of the law several years later, thereby providing new decision-making tools for policy making. Here, the effect immediately after the law is enacted is called one move ahead, and the state reflecting human behavior further ahead is called two moves ahead. In this study, we take up the Labor Contract Act and construct a multi-agent model of an artificial labor market consisting of company agents with Q-learning and worker agents. The experimental results confirmed that the employment termination of fixed-term workers occurred due to the amendment of the law.

Academic Significance and Societal Importance of the Research Achievements

法律は,政府が主導する政策に沿って制定され,社会的,経済的効果をもたらすことが期待される.しかし,必ずしも当初の予想通りの効果がもたらされるとは限らない.この原因は,政策を決定した段階において,法律施行直後の効果の予測(一手先の予測)ができても,さらにその先の人間の行動を反映した予測(二手先の予測)が事前にできないことにある.すなわち,これが実現できれば,それを補うべくより効果的な政策が期待できる.雇い止めの問題は,昨今大きく騒がれている問題である.この問題をシミュレーションによってその原因を確認したことは,社会的意義が大きいと考えることができる.

Report

(4 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (7 results)

All 2022 2021 2020

All Journal Article (2 results) (of which Peer Reviewed: 2 results) Presentation (5 results) (of which Int'l Joint Research: 3 results)

  • [Journal Article] Simulation for labor market using a multi-agent model toward validation of the Amended Labor Contract Act2022

    • Author(s)
      Makoto Nakamura, Shingo Hagiwara, and Ryuichi Matoba
    • Journal Title

      Journal of Artificial Life and Robotics

      Volume: -

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Extension of iterated learning model based on real-world experiment2021

    • Author(s)
      R. Matoba, T. Yonezawa, S. Hagiwara, T. Cooper, M. Nakamura
    • Journal Title

      Artificial Life and Robotics

      Volume: 26 Pages: 228-234

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Presentation] Employment status simulation using multi-agent model2022

    • Author(s)
      Ryuichi Matoba, Koshi Komai, Shingo Hagiwara, and Makoto Nakamura
    • Organizer
      International Symposium on Artificial Life and Robotics (AROB2022)
    • Related Report
      2021 Annual Research Report
  • [Presentation] Simulation for labor market using a multi-agent model towards the validation of the Amended Labor Contract Act2021

    • Author(s)
      Makoto Nakamura, Shingo Hagiwara, Ryuichi Matoba
    • Organizer
      The 26th International Symposium on Artificial Life and Robotics
    • Related Report
      2020 Research-status Report
  • [Presentation] An Approach to Modeling the Social and Economic Effects by the Enactment of Laws2020

    • Author(s)
      Makoto Nakamura, Shingo Hagiwara, Ryuichi Matoba, and Satoshi Tojo
    • Organizer
      Proceedings of the 25th International Symposium on Artificial Life and Robotics 2020 (AROB 25th 2020), Beppu, Japan
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] Extension of Iterated Learning Model Based on Real-World Experiment2020

    • Author(s)
      Ryuichi Matoba, Tomoki Yonezawa, Shingo Hagiwara, Todd Cooper, and Makoto Nakamura
    • Organizer
      Proceedings of the 25th International Symposium on Artificial Life and Robotics 2020 (AROB 25th 2020), Beppu, Japan
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] Simulation of Employment Environment Using Multi-agent Model2020

    • Author(s)
      Ryuichi Matoba, Koshi Komai, Takahiro Nanba, Shingo Hagiwara, and Makoto Nakamura
    • Organizer
      Proceedings of the 25th International Symposium on Artificial Life and Robotics 2020 (AROB 25th 2020), Beppu, Japan
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research

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Published: 2019-07-04   Modified: 2023-01-30  

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