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By Gabriella Pigozzi, Marija Slavkovik, Leendert van der Torre (auth.), Francesca Rossi, Alexis Tsoukias (eds.)

This quantity comprises the papers provided at ADT 2009, the 1st foreign convention on Algorithmic choice concept. The convention used to be held in San Servolo, a small island of the Venice lagoon, in the course of October 20-23, 2009. this system of the convention incorporated oral shows, posters, invited talks, and tutorials.

The convention bought sixty five submissions of which 39 papers have been accredited (9 papers have been posters). the subjects of those papers variety from computational social selection choice modeling, from uncertainty to choice studying, from multi-criteria selection making to online game theory.

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Extra info for Algorithmic Decision Theory: First International Conference, ADT 2009, Venice, Italy, October 20-23, 2009. Proceedings

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First, the agent needs to compute the outcome of the vote between the current state x(t) and each possible alternative x ∈ X. Let X w ⊆ X denote the set of winning alternatives against x(t). For agent i, the set of best proposals is Pi = argmaxx ∈X w Ut (x , i). If the expected utility of the alternatives in Pi is greater than Ut (x(t), i) (the expected utility of the current alternative), then agent i proposes with equi-probability one of the alternatives in Pi . Else, agent i is content with the current alternative and proposes maintaining the status quo (there is no decision to make since x = x(t)).

Manipulating a sporting competition is slightly different to manipulating an election as, in a sporting competition, the voters are also the candidates. A tournament graph describes the outcome of all fair games between opponents. Manipulating a competition therefore modifies not votes but the tournament graph directly. Since it is hard without bribery or similar mechanisms for a team This work is funded by an NSERC Postgraduate Scholarship1 , the Department of Broadband, Communications and Digital Economy2 and the Australian Research Council2 .

Agents can use different currencies). However, we do assume that agents will use their knowledge of the utility of other agents for predicting their behaviour. A game proceeds in successive iterations. At each iteration t, there is a current alternative x(t) (a given allocation, a current bill). , a new allocation, an amendment to the current bill). An agent may propose an alternative that was already proposed in the past; and it may propose to maintain the status quo by proposing x = x(t). The agents vote between x and x(t).

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