论文标题
搜索@主人：一个商业现成的环境，用于调查优化问题
Search@Home: A Commercial Off-the-Shelf Environment for Investigating Optimization Problems
论文作者
论文摘要
搜索启发式方法，尤其是评估驱动的启发式方法（例如进化计算），通常是在模拟中进行的，从而可以探索大型解决方案空间。然而，仿真可能无法真正复制现实世界的条件。但是，搜索启发式方法已被证明是在现实世界中限制的环境中执行的，即使在广泛的解决方案空间中也限制了搜索能力。此外，搜索原位提供了将搜索启发式传播到部署应用程序将面临的确切条件和不确定性的额外好处。软件工程问题可以通过现实环境中的实例化和分析从原位搜索中受益。本文介绍了Search@Home，这是一个包括异质商业现成设备的环境，可快速对现实世界中的优化策略进行快速原型制定。
Search heuristics, particularly those that are evaluation-driven (e.g., evolutionary computation), are often performed in simulation, enabling exploration of large solution spaces. Yet simulation may not truly replicate real-world conditions. However, search heuristics have been proven to be successful when executed in real-world constrained environments that limit searching ability even with broad solution spaces. Moreover, searching in situ provides the added benefit of exposing the search heuristic to the exact conditions and uncertainties that the deployed application will face. Software engineering problems can benefit from in situ search via instantiation and analysis in real-world environments. This paper introduces Search@Home, an environment comprising heterogeneous commercial off-the-shelf devices enabling rapid prototyping of optimization strategies for real-world problems.
