In the field of computer science, there are two major approaches for algorithm design and execution: and . While sequential algorithms follow a step-by-step of execution, s operate on multiple or . Parallel algorithms are particularly useful in scenarios where computational tasks are numerous and can be divided among available processors or threads.
One popular type of parallel algorithm is the model, where multiple agents work together to accomplish a collective task. In this model, each agent acts independently and makes decisions based on its local knowledge and the information provided by other agents. By coordinating their actions, these agents can perform complex tasks more efficiently than a single sequential process. This parallel approach is particularly suitable for tasks that require distributed problem-solving or have a large search space.
