Bayesianism A popular contemporary approach to rationality is based on Bayesian epistemology. Bayesian epistemology sees belief as a continuous phenomenon that comes in degrees. For example, Daniel is relatively sure that the Boston Celtics will win their next match and absolutely certain that two plus two equals four. In this case, the degree of the first belief is weaker than the degree of the second belief. These degrees are usually referred to as credences and represented by numbers between 0 and 1. 0 corresponds to full disbelief, 1 corresponds to full belief and 0.5 corresponds to suspension of belief. Bayesians understand this in terms of probability: the higher the credence, the higher the subjective probability that the believed proposition is true. As probabilities, they are subject to the laws of probability theory. These laws act as norms of rationality: beliefs are rational if they comply with them and irrational if they violate them. For example, it would be irrational to have a credence of 0.9 that it will rain tomorrow together with another credence of 0.9 that it will not rain tomorrow. This account of rationality can also be extended to the practical domain by requiring that agents maximize their subjective expected utility. This way, Bayesianism can provide a unified account of both theoretical and practical rationality.
Bayesianism A popular contemporary approach to rationality is based on Bayesian epistemology. Bayesian epistemology sees belief as a continuous phenomenon that comes in degrees. For example, Daniel is relatively sure that the Boston Celtics will win their next match and absolutely certain that two plus two equals four. In this case, the degree of the first belief is weaker than the degree of the second belief. These degrees are usually referred to as credences and represented by numbers between 0 and 1. 0 corresponds to full disbelief, 1 corresponds to full belief and 0.5 corresponds to suspension of belief. Bayesians understand this in terms of probability: the higher the credence, the higher the subjective probability that the believed proposition is true. As probabilities, they are subject to the laws of probability theory. These laws act as norms of rationality: beliefs are rational if they comply with them and irrational if they violate them. For example, it would be irrational to have a credence of 0.9 that it will rain tomorrow together with another credence of 0.9 that it will not rain tomorrow. This account of rationality can also be extended to the practical domain by requiring that agents maximize their subjective expected utility. This way, Bayesianism can provide a unified account of both theoretical and practical rationality.