Research work · 2016
Behavioral Psychology
International Journal of Psychology
Abstract
Bayes inference (BI) is based on the assumption in which conditional probability of an event can be replaced with the probability of the event.Given a set of hypotheses for events, the probability distribution of the hypotheses is gradually updated dependent on empirical data.By contrast, in the inverse Bayes inference (IBI), a set of hypotheses for events itself can be changed dependent on empirical data.Although IBI has not been referred in cognitive and brain science, both BI and IBI can correspond to the neural process in a brain.In modifying a mathematical sheaf theory by which a set of functions can be pasted over a wholeness, one can implement internal selection of neural activity and global work space.The former and the latter can correspond to BI and IBI, respectively.In my talk we discuss the significance of combination of BI and IBI in making decision.
DOI: 10.1002/ijop.12297