ChatGPT Chats on Computational Experiments: From Interactive Intelligence to Imaginative Intelligence for Design of Artificial Societies and Optimization of Foundational Models

Abstract

Powered by the rapid development of Internet, the penetration of the Internet of Things, the emergence of big data, and the rise of social media, more and more complex systems are exhibiting the characteristics of social, physical, and information fusion. These systems are known as cyber-physical-social systems (CPSS) [1], [2]. These CPSS face unprecedented challenges in design, analysis, management, control and integration due to their involvement with human and social factors [3], [4]. To cope with this challenge, there are two main approaches to CPSS research: 1)Data driven analysis method. Regard complex systems as black boxes, focus on the relationship between inputs and outputs, without modeling and analyzing the complex processes within the system. In the practical application, complex systems tend to be replaced by statistical models based on data and intelligent algorithms, such as convolutional neural network (CNN), recurrent neural networks (RNN), foundation models, etc. The latest ChatGPT (chat generative pretrained transformer) is a typical example of this approach. 2)Knowledge driven analysis method. According to the principle of “simple consistency”, the complex system in practice can be recognized, understood and analyzed by designing and restoring the structure and function of each system component. The computational experiments method is a representative method [5]. Starting from the micro-scale, it cultivates an “artificial society” of the real system in the cyber world. Then, a variety of experiments can be conducted to identify the causal relationship between intervention variables and system emergence to realize the interpretation, understanding, guidance and regulation of macro phenomena.