Automating the Scientific Method

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In February 2008, Kevin Knuth (President, Autonomous Exploration, Inc.) was invited to present a talk titled “Automating the Scientific Method” at the New York Workshop on Computer, Earth, and Space Sciences (CESS 2009) held at the NASA Goddard Institute for Space Studies in New York City NY.  This talk discussed the computational foundation of automated inference and inquiry.  An abstract follows below:

Automating the Scientific Method

Kevin H. Knuth
Associate Professor of Physics and Informatics, University at Albany
President, Autonomous Exploration, Inc.

In the last decade we have seen computer science, statistics, and the earth,
space, life and social sciences come together with a new synergy based on the
common goal of data analysis. These multi-disciplinary interactions have
become necessary as we pursue both high quality data analysis as well as
analysis of extremely large data sets. However, the ultimate goal is more
fundamental than mere data analysis. We aim to automate the scientific method

The scientific method relies on the cyclic application of three activities:
hypothesis generation, inquiry (experimental design) and inference
(data analysis). The majority of our efforts at this point have been focused
on the process of automating inference. However, little attention has been
paid to automating the processes of inquiry and hypothesis generation.

The most scientifically-useful approach to data analysis is model-based.
I will briefly review the methodology behind automating model-based inference
with a focus on Bayesian probability theory. I will then introduce a new
related methodology called the inquiry calculus, which enables the automation
of model-based inquiry. Automated hypothesis (model) generation will be left
for another day, as it is the least advanced of the three technologies. I will
demonstrate the application of automated inference and inquiry with a robotic
scientist that performs its own experiments and analyzes its own data.

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