Reasoning with incomplete and imprecise preferences

Preferences are present in many real life situations but it is often difficult to quantify them giving a precise value. Sometimes preference values may be missing because of privacy reasons or because they are expensive to obtain or to produce. In some other situations the user of an automated system may have a vague idea of whats he wants. In this thesis we considered the general formalism of soft constraints, where preferences play a crucial role and we extended such a framework to handle both incomplete and imprecise preferences. In particular we provided new theoretical frameworks to handle such kinds of preferences. By admitting missing or imprecise preferences, solving a soft constraint problem becomes a different task. In fact, the new goal is to find solutions which are the best ones independently of the precise value the each preference may have. With this in mind we defined two notions of optimality: the possibly optimal solutions and the necessary optimal solutions, which are optimal no matter we assign a precise value to a missing or imprecise preference. We provided several algorithms, bases on both systematic and local search approaches, to find such kind of solutions. Moreover, we also studied the impact of our techniques also in a specific class of problems (the stable marriage problems) where imprecision and incompleteness have a specific meaning and up to now have been tackled with different techniques. In the context of the classical stable marriage problem we developed a fair method to randomly generate stable marriages of a given problem instance. Furthermore, we adapted our techniques to solve stable marriage problems with ties and incomplete lists, which are known to be NP-hard, obtaining good results both in terms of size of the returned marriage and in terms of steps need to find a solution.

Different addictive drug exposure induces selective alterations of the Endogenous Opioid System : modulation of transcription and epigenetic mechanisms

Drug addiction manifests clinically as compulsive drug seeking, and cravings that can persist and recur even after extended periods of abstinence. The fundamental principle that unites addictive drugs is that each one enhances synaptic DA by means that dissociate it from normal behavioral control, so that they act to reinforce their own acquisition. Our attention has focused on the study of phenomena associated with the consumption of alcohol and heroin. Alcohol has long been considered an unspecific pharmacological agent, recent molecular pharmacology studies have shown that acts on different primary targets. Through gene expression studies conducted recently it has been shown that the classical opioid receptors are differently involved in the consumption of ethanol and, furthermore, the system nociceptin / NOP, included in the family of endogenous opioid system, and both appear able to play a key role in the initiation of alcohol use in rodents. What emerges is that manipulation of the opioid system, nociceptin, may be useful in the treatment of addictions and there are several evidences that support the use of this strategy. The linkage between gene expression alterations and epigenetic modulation in PDYN and PNOC promoters following alcohol treatment confirm the possible chromatin remodeling mechanism already proposed for alcoholism. In the second part of present study, we also investigated alterations in signaling molecules directly associated with MAPK pathway in a unique collection of postmortem brains from heroin abusers. The interest was focused on understanding the effects that prolonged exposure of heroin can cause in an individual, over the entire MAPK cascade and consequently on the transcription factor ELK1, which is regulated by this pathway. We have shown that the activation of ERK1/2 resulting in Elk-1 phosphorylation in striatal neurons supporting the hypothesis that prolonged exposure to substance abuse causes a dysregulation of MAPK pathway.