Abstract
The basic ideas of modern decision theory might be used in understanding the adoption and rejection of scientific hypotheses and theories. This chapter discusses the special kinds of scientific or theoretical utilities named “epistemic utilities.” To qualify as a utility, a measure of information must satisfy the usual Von Neumann–Morgenstern utility axioms. Levi's negative results reinforce the larger question whether any approach to induction in terms of epistemic utilities has much hope of success. In addition, the chapter discusses some special measures of semantic information. The first of them is based on a regular and symmetrical measure function that gives each constituent an equal a priori probability. The chapter also defines a priori probability of each state-description. This probability is obtained by dividing the weight of each constituent evenly among the state-descriptions that make this constituent true.
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