This article examines two questions about scientists' search for knowledge. First, which search strategies generate discoveries effectively? Second, is it advantageous to diversify search strategies? We argue pace Weisberg and Muldoon, "Epistemic Landscapes and the Division of Cognitive Labor" (this journal, 2009), that, on the first question, a search strategy that deliberately seeks novel research approaches need not be optimal. On the second question, we argue they have not shown epistemic reasons exist for the division of cognitive labor, identifying the errors that led to their conclusions. Furthermore, we generalize the epistemic landscape model, showing that one should be skeptical about the benefits of social learning in epistemically complex environments.
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机译：本文探讨了有关科学家寻求知识的两个问题。首先，哪种搜索策略有效地产生发现？其次，多样化的搜索策略是否有利？我们认为，Weisberg和Muldoon在“ Epistemic Landscapes and Cognitive Labour”（该期刊，2009年）中提出的步调是，在第一个问题上，刻意寻求新颖研究方法的搜索策略不一定是最优的。关于第二个问题，我们认为他们没有显示出认知工作分工存在的认知原因，指出了导致他们结论的错误。此外，我们推广了认知景观模型，表明人们应该对在认识论上复杂的环境中社会学习的好处持怀疑态度。
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