We develop a framework based on Bayesian model averaging to explain how animals cope with uncertainty about contingencies in classical conditioning experiments. Traditional accoun...
Aaron C. Courville, Nathaniel D. Daw, Geoffrey J. ...
A new language and inference algorithm for stochastic modeling is presented. This work refines and generalizes the stochastic functional language originally proposed by [1]. The l...
This paper investigates theoretically based instructional approaches for organizational training, education and knowledge acquisition for simulation modeling. It proposes differen...
Tajudeen A. Atolagbe, Vlatka Hlupic, Simon J. E. T...
Defining information required by automatic test systems frequently involves a description of system behavior. To facilitate capturing the required behavior information in the cont...
Graphical models of brain functional connectivity have matured from con rming a priori hypotheses to an exploratory tool for discovering unknown connectivity. However, exploratory...