👉 Population computing is a computational paradigm that involves the use of multiple, often loosely connected, processors or agents to solve complex problems. These processors can be physical devices like computers or specialized hardware, or even software agents that operate independently or in a coordinated manner. The populations in this context refer to the diverse set of these agents, each potentially operating with its own local knowledge and resources. By interacting and exchanging information, these agents collaborate to tackle tasks that would be challenging or inefficient for a single processor. This approach is particularly useful for problems that are distributed, dynamic, or require parallel processing, such as optimization, machine learning, and large-scale simulations. The collective intelligence and distributed nature of population computing enable it to handle complex, real-world problems more effectively than traditional centralized computing methods.
