How can you overcome common challenges when working with complex adaptive systems?
Complex adaptive systems (CAS) are dynamic networks of interacting agents that can evolve, learn, and self-organize in response to changing environments. Examples of CAS include ecosystems, markets, social movements, and the human brain. Working with CAS can pose many challenges for researchers, such as uncertainty, unpredictability, emergence, and non-linearity. However, there are also some strategies that can help you overcome these challenges and conduct effective and rigorous research on CAS. In this article, you will learn about some of these strategies, such as: