Kyburg describes his theory as Keynesian and Fisherian (see John Maynard Keynes and Ronald Fisher), a delivery on the promises of Rudolf Carnap and Hans Reichenbach for a logical probability based on reference classes, a reaction to Neyman–Pearson statistics (see Jerzy Neyman, Karl Pearson, and Neyman–Pearson lemma), and neutral with respect to Bayesian confirmational conditionalization.
Kyburg's later major works include Epistemology and Inference (1983), a collection of essays; Theory and Measurement (1984), a response to Krantz–Luce–Suppes–Tversky's Foundations of Measurement; and Science and Reason (1990), which seeks to allay Karl Popper's and Bruno de Finetti's concerns that empirical data could not confirm a universally quantified scientific axiom (e.g., F = ma).
[1] Kyburg owned a farm in Lyons, New York where he raised Angus cattle with his wife, Sarah, and promoted wind turbine systems for energy-independent farmers.
Several full professors of philosophy today were once undergraduates of Henry Kyburg, including Daniel Dennett, Robert Stalnaker, Rich Thomason, Teddy Seidenfeld, and William L. Harper.
His AI dissertation students were Ronald Loui, Bulent Murtezaoglu, and Choh Man Teng, and postdoctoral visitor Fahiem Bacchus.
His philosophy students included daughter Alice Kyburg, Mariam Thalos, Gregory Wheeler, William Harper, Abhaya Nayak, Prashanta Bandyopadhaya, in addition to those listed above.
This is like a level of confidence, except that Neyman–Pearson theory is prohibited from retrospective calculation and post-observational acceptance, while Kyburg's epistemological interpretation of probability licenses both.