Propositional update operators based on formula/literal dependence

International audienceWe present and study a general family of belief update operators in a propositional setting. Its operators are based on formula/literal dependence, which is more fine-grained than the notion of formula/variable dependence that was proposed in the literature: formula/variable dependence is a particular case of formula/literal dependence. Our update operators are defined according to the "forget-then-conjoin" scheme: updating a belief base by an input formula consists in first forgetting in the base every literal on which the input formula has a negative influence, and then conjoining the resulting base with the input formula. The operators of our family differ by the underlying notion of formula/literal dependence, which may be defined syntactically or semantically, and which may or may not exploit further information like known persistent literals and pre-set dependencies. We argue that this allows to handle the frame problem and the ramification problem in a more appropriate way. We evaluate the update operators of our family w.r.t. two important dimensions: the logical dimension, by checking the status of the Katsuno-Mendelzon postulates for update, and the computational dimension, by identifying the complexity of a number of decision problems (including model checking, consistency and inference), both in the general case and in some restricted cases, as well as by studying compactability issues. It follows that several operators of our family are interesting alternatives to previous belief update operators

How to Progress a Database (and Why) I. Logical Foundations

One way to think about STRIPS is as a mapping from databases to databases, in the following sense: Suppose we want to know what the world would be like if an action, represented by the STRIPS operator ff, were done in some world, represented by the STRIPS database D 0 . To find out, simply perform the operator ff on D 0 (by applying ff's elementary add and delete revision operators to D 0 ). We describe this process as progressing the database D 0 in response to the action ff. In this paper, we consider the general problem of progressing an initial database in response to a given sequence of actions. We appeal to the situation calculus and an axiomatization of actions which addresses the frame problem (Reiter [13], Lin and Reiter [8]). This setting is considerably more general than STRIPS. Our results concerning progression are mixed. The (surprising) bad news is that, in general, to characterize a progressed database we must appeal to second order logic. The good news is that there..

Learning non-monotonic Logic Programs to Reason about Actions and Change

[Resumen] El objetivo de esta tesis es el diseño de métodos de aprendizaje automático capaces de encontrar un modelo de un sistema dinámico que determina cómo las propiedades del sistema con afectadas por la ejecución de acciones, Esto permite obtener de manera automática el conocimiento específico del dominio necesario para las tareas de planficación o diagnóstico así como predecir el comportamiento futuro del sistema. La aproximación seguida difiere de las aproximaciones previas en dos aspectos. Primero, el uso de formalismos no monótonos para el razonamiento sobre acciones y el cambio con respecto a los clásicos operadores tipo STRIPS o aquellos basados en formalismos especializados en tareas muy concretas, y por otro lado el uso de métodos de aprendizaje de programas lógicos (Inductive Logic Programming). La combinación de estos dos campos permite obtener un marco declarativo para el aprendizaje, donde la especificación de las acciones y sus efectos es muy intuitiva y natural y que permite aprender teorías más expresivas que en anteriores aproximaciones