"[This conference] will involve researchers from such disparate fields as decision theory, discrete mathematics, theoretical computer science, economics, and artificial intelligence, aiming to improve decision support in the presence of massive data bases, partial and/or uncertain information, and distributed decision makers."

When we have an infinite set of hypotheses, the expected utility of some action is determined by an infinite series. It’s important for that series to converge, or else we won’t be able to compare the expected utilities of two different actions.

Not every change is an improvement, but every improvement is necessarily a change. If we only admit small local errors, we will only make small local changes. We could move so much faster.

Possibilities of modeling pathological expressions in formal and natural languages. May in part be relevant for models where classical decision theory breaks down due to infinite recursion.