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ABDUCTIVE ACTIVE LEARNING. "At the beginning of any investigation, the Robot Scientist has not discovered any information, therefore all possible hypotheses are equally valid. As the directed discovery process continues, each new observation (or experiment/interpretation cycle) will invalidate some of the hypotheses, thereby excluding incorrect discoveries. The experiment selection process aims to choose the experiment most likely to refute the most hypotheses." https://lnkd.in/dUdRjJH View in LinkedIn

BIG DATA MINING. "Condensing rules from raw data has long been considered the province of human intuition, not machine intelligence. It could foreshadow an age in which scientists and programs work as equals to decipher datasets too complex for human analysis." (Eureqa). https://lnkd.in/dEC3j_P View in LinkedIn

ACTIVE LEARNING "uses abductive logic programming to generate valid hypotheses that explain the observations; and uses these hypotheses to determine the next most informative experiment." https://lnkd.in/dUdRjJH View in LinkedIn

CHANGING MANY VARIABLES TOGETHER. "In most of science, you try to keep everything constant except for one variable. You turn one knob at a time, and see how the system responds. That’s wonderful for linear systems...But most biology is complex and non-linear. Emergent behaviors are very hard to understand unless you turn many knobs at a time, and we can’t figure out which knobs to turn. So we’re going to let Eureqa pick them.” https://lnkd.in/dEC3j_P View in LinkedIn

ACTIVE LEARNING. "The Robot Scientist makes use of an iterative approach to experimentation, where knowledge acquired from a previous iteration is used to guide the next experimentation step. This is a process known as Active Learning, where the learner can plan its own agenda, i.e. decide how best to improve its knowledge base and how to go about acquiring this information." https://lnkd.in/dUdRjJH View in LinkedIn

SCRAPYARD MINING. "This knowledge will initially correspond to the goals of the scientific task, but increasingly the internet repositories that are often constructed to store the data have become the focus of less directed scientific study, where "hidden" knowledge not originally anticipated by the goals of the scientific task may be found. However, this "scrapyard" approach is partly a result of overexperimentation where many unnecessary experiments were conducted along with the potentially informative ones." https://lnkd.in/dUdRjJH View in LinkedIn

BIOINFORMATICS DATA MINING. "It has become typical practice in Bioinformatics to separate the data collection or experimentation process and the understanding process, where large numbers of experiments are conducted and then specially designed data mining tools are used to identify correlations in the data that might represent hitherto undiscovered scientific knowledge." https://lnkd.in/dUdRjJH View in LinkedIn

STEP FORWARD. “This Robot Scientist will be capable of initiating >1,000 experiments, and making >200,000 observations a day. Robot Scientists provide a unique test bed for the development of methodologies for the curation and annotation of scientific experiments: because the experiments are conceived and executed automatically by computer, it is possible to completely capture and digitally curate all aspects of the scientific process.” https://lnkd.in/dQyqwwv View in LinkedIn

"GRAFFITI.PC is a conjecture-making computer program whose design was strongly influenced by the design of the conjecture-making program Graffiti. The program Graffiti was created in the mid 1980's by Siemion Fajtlowicz of the University of Houston. As his student in the early 1990's, I contributed to the development of the most recent versions of Graffiti." https://lnkd.in/dEMGmTW View in LinkedIn

RESEARCH OUTPUT. 92 research articles inspired by Graffiti. https://lnkd.in/d_iPp8q View in LinkedIn