Abstract

Bayesian decision theory in its classical formulation supposes that for any rational agent and for any possible state x of the world, there is a number P(x). which represents the agent’s judgment of the probability of x. Similarly, the theory assumes that for any possible outcome y of the agent’s actions, there is a number u(y) which represents the utility or value of y to the agent. Given these assumptions, the theory is able to define the expected value for the agent of any act. Bayesian decision theory then recommends that the agent should choose, from amongst the available acts, one which has maximal expected utility.The assumption that an agent has a determinate personal probability function has often been attacked.