Imagine you're a new quant researcher at a high-frequency trading (HFT) firm. Your boss gives you a crucial task: from a pool of 100 new trading strategy prototypes, select the single best one for live-testing. These strategies will be presented to you one by one, in sequence. For each strategy, you will only see its expected return and risk profile, and you must immediately decide whether to accept or reject it. Once you reject a strategy, you cannot go back to it. Once you accept a strategy, the selection process ends. Your goal is to maximize the probability of selecting the absolute best strategy (i.e., the strategy that would perform optimally among all 100). How would you design your decision rule to achieve this? Please walk me through your thought process in detail.

你是一家高频交易公司的新晋策略研究员。老板给你一个任务：从即将发布的100个新的交易策略原型中，挑选一个最佳策略进行实盘测试。这些策略会按顺序逐一展示给你，你每次只能看到当前策略的预期收益和风险评分，并必须立即决定是否选择它。一旦你拒绝了一个策略，就不能再回头选择它。一旦你选择了一个策略，过程就结束了。你的目标是最大化你选中“最佳”策略的概率（即在所有100个策略中排名第一的策略）。你会如何设计你的决策规则？请详细阐述你的思考过程。