Abduction, of inference to the best explanation, is a form of inference that goes from data describing something to a hypothesis that best explains or accounts for the data.
D is a collection of data (facts, observations, givens).
H explains D (would, if true, explain D).
No other hypothesis can explain D as well as H does.
... Therefore, H is probably true.
– Josephson & Josephson, Abductive Inference
The work described in my Ph.D. dissertation (Fischer 1991) It is the outcome of seven years of research focusing on abductive explanation generation and involving the departments of computer and information science, industrial and systems engineering, pathology, and allied medical professions at The Ohio State University. In the first phase of my work, I characterized abductive problem solving and performed a comparative analysis of two abductive problem solvers (Smith and Fischer 1990). Thus, I implemented two cognitively plausible heuristics to tackle the complexity of abductive reasoning and successfully experimented with them. This work, originally applied to the domain of alloantibody identification, was generalized to domain-independent abductive problem solving. Abduction, that is, inference to a hypothesis that best explains a set of data, appears to be ubiquitous in cognition.
There are however, a variety of different approaches that claim to capture the true nature of this concept. One reason for this diversity lies in the fact that abductive reasoning occurs in a multitude of contexts. It concerns cases that cover the simplest selection of already existing hypotheses to the generation of new concepts in science. It also concerns cases where the observation is puzzling because it is novel versus cases in which the surprise concerns an anomalous observation. For example, if we wake up, and the lawn is wet, we might explain this observation by assuming that it must have rained or that the sprinklers have been on.
Baba Vanga, a blind Bulgarian mystic who died in 1996, is said to have predicted a huge scientific discovery for 2018: a new form of energy on the planet Venus. With no planned missions to Venus this year, her prediction is not expected to come to fruition. More than 20 years after her death, people are waiting to see if Baba Vanga's prophecies for 2018 will come to pass. They reportedly include the Venus discovery, as well as China passing the United States in economic power, although it is unclear where these statements are coming from. Baba Vanga, whose real name was Vangelia Gushterova, was blinded as a child during a tornado.
The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud computing technologies. In The Fourth Paradigm: Data-Intensive Scientific Discovery, the collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized. "The impact of Jim Gray's thinking is continuing to get people to think in a new way about how data and software are redefining what it means to do science." "I often tell people working in eScience that they aren't in this field because they are visionaries or super-intelligent--it's because they care about science and they are alive now.
Today in Entertainment: Seth Meyers finds a new law of Trump physics; Jonathan Demme brought out performers' best Here's what's new and interesting in entertainment and the arts: The science on the Trump administration is a little closer to settled. "Late Night with Seth Meyers" offered a deep dive Wednesday night into the administration's apparent fondness for executive orders -- the president has signed 30 so far -- and highlighted how Trump the candidate was less enamored of the practice than Trump the president appears to be. "It is at this point like a law of physics," Meyers said at the beginning of one of his "A Closer Look" segments. Putting the comedy in some context: Presidents Clinton, George W. Bush and Obama averaged 45.5, 36.4 and 34.5 executive orders per year, respectively, over their eight years each in office, according to the American Presidency Project at UCSB.
Last year, there were more than 1.2 million new papers published in the biomedical sciences alone, bringing the total number of peer-reviewed biomedical papers to over 26 million. Some recent studies found that the majority of biomedical papers were irreproducible. Automation of the scientific process could greatly increase the rate of discovery. That huge possibility hinges on an equally huge question: Can scientific discovery really be automated?
"Our unwavering commitment to promoting the progress of science has opened new windows on the universe, made possible new industries, and improved the lives of all Americans," MIT Vice President for Research Maria T. Zuber told members of the U.S. House of Representatives at a March 21 hearing of the Subcommittee on Research and Technology of the Committee on Science, Space, and Technology, speaking in her role as chair of the National Science Board (NSB). "The question before us," she continued, "is will the world's richest, most powerful nation continue to invest in our future? Do we still want to be the first to know, to understand, to discover, to invent?" The 25-member NSB is the governing board for the National Science Foundation (NSF). Zuber appeared before the subcommittee at the second in a series of hearings examining the foundation's role in the federal research enterprise.
Several institutions are embroiled in a legal dispute over the foundational patent rights to CRISPR-Cas9 gene-editing technology, and it may take years for their competing claims to be resolved (1–4). But even before ownership of the patents is finalized, the institutions behind CRISPR have wasted no time capitalizing on the huge market for this groundbreaking technology by entering into a series of license agreements with commercial enterprises (see the figure). With respect to the potentially lucrative market for human therapeutics and treatments, each of the key CRISPR patent holders has granted exclusive rights to a spinoff or "surrogate" company formed by the institution and one of its principal researchers (5, 6). Although this model, in which a university effectively outsources the licensing and commercialization of a valuable patent portfolio to a private company, is not uncommon in the world of university technology transfer, we suggest it could rapidly bottleneck the use of CRISPR technology to discover and develop useful human therapeutics.
A more historical-cognitive approach was the aim of the work on BACON, which rediscovered various scientific laws by finding patterns in numerical data (Langley, Simon, Bradshaw & Zytkow, 1987). Simon's early work on finding patterns in sequences (Simon & Kotovsky, 1963) was extended in BACON to heuristic search for patterns in numerical data. The most creative of BACON's abilities was the decomposition of relational data to conjecture intrinsic properties in one or more of the objects engaging in the relations. This step went beyond curve-fitting and was based on the metaphysical assumption that an entity's relational properties are caused by its intrinsic properties. In addition to the data-driven tasks modeled in BACON, the group also investigated theory-driven discovery in STAHL.