Summary of Next-generation Simulation Illuminates Scientific Problems Of Organised Complexity, by Cheng Wang et al.
Next-Generation Simulation Illuminates Scientific Problems of Organised Complexity
by Cheng Wang, Chuwen Wang, Wang Zhang, Shirong Zeng, Yu Zhao, Ronghui Ning, Changjun Jiang
First submitted to arxiv on: 18 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper revisits the classification of scientific problems, acknowledging that unresolved issues persist despite advances in data-driven methodologies. It argues that novel paradigms are necessary to tackle these challenges, particularly those of organized complexity. The authors propose a promising approach: integrating different paradigms through next-generation simulation (NGS) and sophisticated behavioural simulation (SBS). SBS is based on foundational models simulating complex systems like social systems with human strategies and behaviors. This integration of paradigms positions NGS as a potential solution for problems of organized complexity. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial intelligence is changing the way scientists do research, but some big problems still need to be solved. This paper looks back at how scientists have approached these challenges in the past and suggests a new way forward. It says that we need to bring together different approaches to solve really complicated problems. The authors propose using something called next-generation simulation (NGS) and sophisticated behavioural simulation (SBS) to help us make progress. |
Keywords
» Artificial intelligence » Classification