通智测试——基于动态具身物理社会交互环境的通用人工智能测试  

The Tong Test:Evaluating Artificial General Intelligence Through Dynamic Embodied Physical and Social Interactions

作　　者：Yujia Peng Jiaheng Han Zhenliang Zhang Lifeng Fan Tengyu Liu Siyuan Qi Xue Feng Yuxi Ma Yizhou Wang Song-Chun Zhu 

机构地区：[1]National Key Laboratory of General Artificial Intelligence,Beijing Institute for General Artificial Intelligence,Beijing 100086,China [2]Institute for Artificial Intelligence,Peking University,Beijing 100871,China [3]Beijing Key Laboratory of Behavior and Mental Health,School of Psychological and Cognitive Sciences,Peking University,Beijing 100871,China [4]School of Intelligence Science and Technology,Peking University,Beijing 100871,China [5]School of Computer Science,Peking University,Beijing 100871,China

出　　处：《Engineering》2024年第3期12-22,共11页工程（英文）

基　　金：supported by the National Key Research and Development Program of China (2022ZD0114900).

摘　　要：The release of the generative pre-trained transformer(GPT)series has brought artificial general intelligence(AGI)to the forefront of the artificial intelligence(AI)field once again.However,the questions of how to define and evaluate AGI remain unclear.This perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions(DEPSI).More specifically,we propose five critical characteristics to be considered as AGI benchmarks and suggest the Tong test as an AGI evaluation system.The Tong test describes a value-and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI,allowing for infinite task generation.We contrast the Tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized,quantitative,and objective benchmarks and evaluation of AGI.

关 键 词：Artificial general intelligence Artificial intelligence benchmark Artificial intelligence evaluation Embodied artificial intelligence Value alignment Turing test CAUSALITY 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]