AI Agent as Urban Planner: Steering Stakeholder Dynamics in Urban Planning via Consensus-based Multi-Agent Reinforcement Learning

no code implementations • 25 Oct 2023 • Kejiang Qian, Lingjun Mao, Xin Liang, Yimin Ding, Jin Gao, Xinran Wei, Ziyi Guo, Jiajie Li

By integrating Multi-Agent Reinforcement Learning, our framework ensures that participatory urban planning decisions are more dynamic and adaptive to evolving community needs and provides a robust platform for automating complex real-world urban planning processes.

Decision Making Multi-agent Reinforcement Learning +1

AI Nushu: An Exploration of Language Emergence in Sisterhood -Through the Lens of Computational Linguistics

no code implementations • 18 Oct 2023 • Yuqian Sun, Yuying Tang, Ze Gao, Zhijun Pan, Chuyan Xu, Yurou Chen, Kejiang Qian, Zhigang Wang, Tristan Braud, Chang Hee Lee, Ali Asadipour

This paper presents "AI Nushu," an emerging language system inspired by Nushu (women's scripts), the unique language created and used exclusively by ancient Chinese women who were thought to be illiterate under a patriarchal society.