Rational Randomness

摘要: Abstract Probabilistic models of cognitive development indicate the ideal solutions to computational problems that children face as they try make sense their environment. Under this approach, children's beliefs change result a single process: observing new data and drawing appropriate conclusions from those via Bayesian inference. However, such typically leave open question what mechanisms might allow finite minds human perform complex computations required by In chapter, we highlight one potential mechanism: sampling probability distributions. We introduce idea approximating inference Monte Carlo methods, outline key ideas behind review evidence have prerequisites for using these methods. As result, identify second factor should be taken into account in explaining development—the nature are used belief revision.