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We study the problem of online rank elicitation, assuming that rankings of a set of alternatives obey the Plackett-Luce distribution. Following the setting of the dueling bandits problem, the learner is allowed to query pairwise comparisons between alternatives, i.e., to sample pairwise marginals of the distribution in an online fashion. Using this(More)
In this paper, we present a CBR approach for implementing an agent playing the well-known Angry Birds game. We adopt a preference-based procedure for constructing the case base, collecting experience from a random agent that continually explores the problemsolution space and improves the quality of already found solutions. As the retrieve phase involves(More)
The weighted feedback arc set problem on tournaments (WFAS-T) is defined by a weighted tournament graph whose nodes represents the teams/items, and the goal is to find a ranking over the teams that minimizes the sum of the weights of the feedback arcs. We consider the probabilistic version of WFAS-T, in which the weights of the directed edges between every(More)
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