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New heuristic (1) is used to prefer revision to premises that support relatively weak generalized beliefs.
— Pat Langley
New heuristic (1) is used to prefer revision to premises that support relatively weak generalized beliefs.
Science is a seamless web: each idea spins out to a new research task, and each research finding suggests a repair or an elaboration of the network of theory. Most of the links connecting the nodes are short, each attaching to its predecessors. Weaving our way through the web, we stop from time to time to rest and survey the view — and to write a paper or a book.
In the scientist’s house are many mansions... Outsiders often regard science as a sober enterprise, but we who are inside see it as the most romantic of all callings. Both views are right. The romance adheres to the processes of scientific discovery, the sobriety to the responsibility for verification...
BACON.4 does not have heuristics for considering trigonometric functions of variables directly . Thus, in the run described here we simply told the system to examine the sines. In the following chapter we will see how BACON can actually arrive at the sine term on its own in a rather subtle manner.
In all of these cases, the error arose from accepting “loose” fits of a law to data, and the later, correct formulation provided a law that fit the data much more closely. If we wished to simulate this phenomenon with BACON, we would only have to set the error allowance generously at the outset, then set stricter limits after an initial law had been found.
As aims to address larger, more complex tasks, the problem of focusing on the most relevant information in a potentially overwhelming quantity of data has become increasingly important.
Given a sample of data S, a learning algorithm L, and a feature set A, feature xi , is incrementally useful to L with respect to A if the accuracy of the hypothesis that L produces using the feature set {xi} ∪ A is better than the accuracy achieved using just the feature set A.
