Provides a precise language and graphic notation for analyzing decision making in the presence of uncertainty.

A generalization of the Bayesian theory of subjective probability which does not require exact probabilities for each question of interest; can yield answers which contradict those arrived at using probability theory.

E. T. Jaynes' thoughts on physics, probability, and on what he learned during his 50 years as a researcher.

"The bulk of human knowledge is organized around causal, not probabilistic relationships, and the grammar of probability calculus is insufficient for capturing those relationships."

The first four axioms are consistent with both quantum theory and classical probability theory. Axiom 5 (which requires that there exists continuous reversible transformations between pure states) rules out classical probability theory.

Peter Norvig shows how to achieve 80 to 90% accuracy for English spelling correction in 20 lines of python code.

The two envelopes problem is a puzzle or paradox within the subjectivistic interpretation of probability theory; more specifically within Bayesian decision theory. This is still an open problem among the subjectivists as no consensus has been reached yet.

One of the justifications for the use of Bayesian probability theory. Probability is interpreted as a formal system of logic, the natural extension of Aristotelian logic into the realm of reasoning in the presence of uncertainty.

The major theme of the thesis is to develop a mathematical foundation of Artificial Intelligence and, more specifically, to develop a theory for rational agents acting optimally in any environment.

Can we forecast the probability of an arbitrary sequence of events happening so that the stated probability of an event happening is close to its empirical probability?

If n possibilities are indistinguishable, then each possibility should be assigned the probability 1/n. For continuous variables, the principle of indifference does not indicate which variable is to have a uniform epistemic probability distribution.