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Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment (2312.11813v1)

Published 19 Dec 2023 in cs.AI and cs.CY

Abstract: Urban environments, characterized by their complex, multi-layered networks encompassing physical, social, economic, and environmental dimensions, face significant challenges in the face of rapid urbanization. These challenges, ranging from traffic congestion and pollution to social inequality, call for advanced technological interventions. Recent developments in big data, artificial intelligence, urban computing, and digital twins have laid the groundwork for sophisticated city modeling and simulation. However, a gap persists between these technological capabilities and their practical implementation in addressing urban challenges in an systemic-intelligent way. This paper proposes Urban Generative Intelligence (UGI), a novel foundational platform integrating LLMs into urban systems to foster a new paradigm of urban intelligence. UGI leverages CityGPT, a foundation model trained on city-specific multi-source data, to create embodied agents for various urban tasks. These agents, operating within a textual urban environment emulated by city simulator and urban knowledge graph, interact through a natural language interface, offering an open platform for diverse intelligent and embodied agent development. This platform not only addresses specific urban issues but also simulates complex urban systems, providing a multidisciplinary approach to understand and manage urban complexity. This work signifies a transformative step in city science and urban intelligence, harnessing the power of LLMs to unravel and address the intricate dynamics of urban systems. The code repository with demonstrations will soon be released here https://github.com/tsinghua-fib-lab/UGI.

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Introduction

Urban environments are mini-universes of complexity, teeming with activity and life spanning across physical, social, economic, and environmental realms. With the advent of big data, urban computing, and AI technologies, there's been a notable push forward in our ability to capture and analyze the intense intricacy of cities. The proposed concept of Urban Generative Intelligence (UGI) takes this to the next level by integrating LLMs with city-specific data to navigate urban challenges in an intelligent way.

Urban Systems and Challenges

Cities represent a network of interactions—each element, from buildings to businesses and beyond, is interwoven with the rest to form the vibrant quilt of urban life. Economic vitality, resource management, and environmental sustainability are all goals of an efficiently functioning city. This is further complicated by factors like social inequalities and ongoing urbanization, making the management of these entities a Herculean task necessitated by an increasingly complex global landscape.

The Power of UGI and CityGPT

UGI encompasses a powerful new platform empowering analytical agents in an articulated cityscape environment. At the heart lies CityGPT, an LLM tailored to digest multi-source, city-specific data ranging from geographic information to human social behavior. These agents, armed with this foundational model, simulate tasks like urban planning and policy-making within triggered urban simulations. UGI can recreate and interact with numerous aspects of city life, learning and evolving as they interact with the multi-faceted digital infrastructure of city simulation and knowledge graphs.

Future Urban Intelligence

The capabilities of UGI translate into real-world advancement in urban intelligence. As these intelligent agents learn from environmental feedback and interact with each other within digital urban confines, they can assist in designing transportation systems, develop smart economic strategies, and facilitate social interactions—all through the CityGPT's expansive understanding of urban dynamics.

In paving the way for a smarter and more connected future, UGI represents a transformative leap in understanding urban complexity through the lens of artificial intelligence. It heralds an age where the intelligent simulation of city systems fosters sustainable development and new forms of urban living yet to be imagined.

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Authors (5)
  1. Fengli Xu (47 papers)
  2. Jun Zhang (1008 papers)
  3. Chen Gao (136 papers)
  4. Jie Feng (103 papers)
  5. Yong Li (628 papers)
Citations (18)
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