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Coalition formation is studied in a setting where agents take part to a group decision-making scenario and where their preferences are expressed via weighted propositional logic, in particular by considering formulas consisting of conjunctions of literals only. Interactions among agents are constrained by an underlying social environment and each agent is associated with a specific social factor determining to which extent she prefers staying in a coalition with other agents. In particular, the utilities of the agents depend not only on their absolute preferences but also on the number of "neighbors" occurring with them in the coalition that emerged. Within this setting, the computational complexity of a number of relevant reasoning tasks is studied, by charting a clear picture of the intrinsic difficulty of finding "agreements" among the agents. Specific algorithmic approaches to reason about such social environments are proposed under the utilitarian perspective, where the collective utility of a coalition is the sum of the utilities of the individuals, as well as under the egalitarian perspective, with the goal being to maximize the utility of the least satisfied agent. These algorithms have been implemented and results of experimental activity are discussed, too. [ABSTRACT FROM AUTHOR]

Coalition formation is studied in a setting where agents take part to a group decision-making scenario and where their preferences are expressed via weighted propositional logic, in particular by considering formulas consisting of conjunctions of literals only. Interactions among agents are constrained by an underlying social environment and each agent is associated with a specific social factor determining to which extent she prefers staying in a coalition with other agents. In particular, the utilities of the agents depend not only on their absolute preferences but also on the number of "neighbors" occurring with them in the coalition that emerged. Within this setting, the computational complexity of a number of relevant reasoning tasks is studied, by charting a clear picture of the intrinsic difficulty of finding "agreements" among the agents. Specific algorithmic approaches to reason about such social environments are proposed under the utilitarian perspective, where the collective utility of a coalition is the sum of the utilities of the individuals, as well as under the egalitarian perspective, with the goal being to maximize the utility of the least satisfied agent. These algorithms have been implemented and results of experimental activity are discussed, too. [ABSTRACT FROM AUTHOR]

The proliferation of information available on the world wide web and the new emerging technologies that have reduced the barriers in organizing and publishing documents, have made the support for navigation and personalization of web sites an appealing and promising task for the AI community. Making the process of retrieving relevant documents easier is one of the most challenging activities in the design of modern sites and goes beyond any particular domain. This paper proposes a new technique for Web navigation based on current algorithms used in Recommendation Systems. Our approach identifies really relevant documents adopting methodologies similar to those successfully used in current search engines. The effectiveness and the validity of our technique have been shown by several experiments. [ABSTRACT FROM AUTHOR]