Confirmation, decision, and evidential probability
Henry Kyburgâs theory of Evidential Probability offers a neglected tool for approaching problems in confirmation theory and decision theory. I use Evidential Probability to examine some persistent problems within these areas of the philosophy of science. Formal tools in general and probability theory in particular have great promise for conceptual analysis in confirmation theory and decision theory, but they face many challenges. In each chapter, I apply Evidential Probability to a specific issue in confirmation theory or decision theory. In Chapter 1, I challenge the notion that Bayesian probability offers the best basis for a probabilistic theory of evidence. In Chapter 2, I criticise the conventional measures of quantities of evidence that use the degree of imprecision of imprecise probabilities. In Chapter 3, I develop an alternative to orthodox utility-maximizing decision theory using Kyburgâs system. In Chapter 4, I confront the orthodox notion that Nelson Goodmanâs New Riddle of Induction makes purely formal theories of induction untenable. Finally, in Chapter 5, I defend probabilistic theories of inductive reasoning against John D. Nortonâs recent collection of criticisms. My aim is the development
Peden, William John
Confirmation, decision, and evidential probability. Henry Kyburgâs theory of Evidential Probability offers a neglected tool for approaching problems in confirmation theory and decision theory. I use Evidential Probability to examine some persistent problems within these areas of the philosophy of science. Formal tools in general and probability theory in particular have great promise for conceptual analysis in confirmation theory and decision theory, but they face many challenges. In each chapter, I apply Evidential Probability to a specific issue in confirmation theory or decision theory. In Chapter 1, I challenge the notion that Bayesian probability offers the best basis for a probabilistic theory of evidence. In Chapter 2, I criticise the conventional measures of quantities of evidence that use the degree of imprecision of imprecise probabilities. In Chapter 3, I develop an alternative to orthodox utility-maximizing decision theory using Kyburgâs system. In Chapter 4, I confront the orthodox notion that Nelson Goodmanâs New Riddle of Induction makes purely formal theories of induction untenable. Finally, in Chapter 5, I defend probabilistic theories of inductive reasoning against John D. Nortonâs recent collection of criticisms. My aim is the development
confirmation decision evidential probability henry theory evidential probability offer neglected tool approach_problem confirmation theory decision theory use evidential probability examine persistent problem within_area philosophy_science formal tool general probability theory particular great promise conceptual analysis confirmation theory decision theory face many challenge apply evidential probability specific_issue confirmation theory decision theory challenge_notion bayesian probability offer best basis probabilistic theory evidence criticise conventional measure quantity evidence use degree imprecise probability develop_alternative orthodox utility decision theory use system confront orthodox notion new induction make purely formal theory induction untenable finally defend probabilistic theory inductive reason john recent collection criticism aim development