This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 1–1 of 1 papers
使用済み家電の回収のマルチエージェントシミュレーション
(著者不明)
This paper analyzes the efficient collection of used home appliances using multi-agent simulation. It explores optimal collection routes and schedules under cooperative and competitive agent scenarios, demonstrating the feasibility of reduc…
Browse by Topic