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The Robot Scientist Project

机译:机器人科学家计划

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摘要

We are interested in the automation of science for both philosophical and technological reasons. To this end we have built the first automated system that is capable of automatically: originating hypotheses to explain data, devising experiments to test these hypotheses, physically running these experiments using a laboratory robot, interpreting the results, and then repeat the cycle. We call such automated systems "Robot Scientists". We applied our first Robot Scientist to predicting the function of genes in a well-understood part of the metabolism of the yeast S. cerevisiae. For background knowledge, we built a logical model of metabolism in Prolog. The experiments consisted of growing mutant yeast strains with known genes knocked out on specified growth media. The results of these experiments allowed the Robot Scientist to test hypotheses it had abductively inferred from the logical model. In empirical tests, the Robot Scientist experiment selection methodology outperformed both randomly selecting experiments, and a greedy strategy of always choosing the experiment of lowest cost; it was also as good as the best humans tested at the task. To extend this proof of principle result to the discovery of novel knowledge we require new hardware that is fully automated, a model of all of the known metabolism of yeast, and an efficient way of inferring probable hypotheses. We have made progress in all of these areas, and we are currently 6building a new Robot Scientist that we hope will be able to automatically discover new biological knowledge.
机译:出于哲学和技术方面的原因,我们对科学的自动化感兴趣。为此,我们构建了第一个能够自动运行的自动化系统:提出假设以解释数据,设计实验以测试这些假设,使用实验室机器人对这些实验进行物理运行,解释结果,然后重复该循环。我们称这种自动化系统为“机器人科学家”。我们应用了我们的第一位机器人科学家来预测酵母酿酒酵母代谢中一个被充分理解的部分中的基因功能。对于背景知识,我们在Prolog中建立了新陈代谢的逻辑模型。该实验由在特定生长培养基上敲除已知基因的突变酵母菌株组成。这些实验的结果使机器人科学家可以检验其从逻辑模型中推断出的假设。在经验测试中,机器人科学家的实验选择方法要优于随机选择的实验和总是选择成本最低的实验的贪婪策略。它也和任务中测试过的最好的人一样好。为了将这种原理性验证结果扩展到发现新知识,我们需要完全自动化的新硬件,所有已知的酵母新陈代谢的模型以及推断可能假设的有效方法。我们在所有这些领域都取得了进展,目前我们正在建立一个新的机器人科学家6,我们希望它将能够自动发现新的生物学知识。

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