La División Académica de Ciencias de la Computación lo invitan a su 2o. Seminario Recursivo "Choosing with unknown causal information: Action-outcome probabilities for decision making can be grounded in causal models" impartido por el Ph.D. Mauricio González Soto, exalumno de la Licenciatura en Matemáticas aplicadas.
Abstract:Decision-making under uncertainty and causal thinking are fundamental aspects of intelligent reasoning. Decision-making has been well studied when the available information is considered at the associative (probabilistic) level. The classical Theorems of von Neumann-Morgenstern and Savage provide a formal criterion for rational choice using associative information: maximize expected utility.In this work, we will show how the probabilities for decision-making can be grounded in causal models by considering decision problems in which the available actions and consequences are causally connected. In this setting, actions are regarded as an intervention over a causal model.