5,787 research outputs found
A network-based rating system and its resistance to bribery
We study a rating system in which a set of individuals (e.g., the customers of a restaurant) evaluate a given service (e.g, the restaurant), with their aggregated opinion determining the probability of all individuals to use the service and thus its generated revenue. We explicitly model the influence relation by a social network, with individuals being influenced by the evaluation of their trusted peers. On top of that we allow a malicious service provider (e.g., the restaurant owner) to bribe some individuals, i.e., to invest a part of his or her expected income to modify their opinion, therefore influencing his or her final gain. We analyse the effect of bribing strategies under various constraints, and we show under what conditions the system is bribery-proof, i.e., no bribing strategy yields a strictly positive expected gain to the service provider
Aggregating Dependency Graphs into Voting Agendas in Multi-Issue Elections
Many collective decision making problems have a
combinatorial structure: the agents involved must
decide on multiple issues and their preferences over
one issue may depend on the choices adopted for
some of the others. Voting is an attractive method
for making collective decisions, but conducting a
multi-issue election is challenging. On the one hand,
requiring agents to vote by expressing their preferences
over all combinations of issues is computationally
infeasible; on the other, decomposing the
problem into several elections on smaller sets of
issues can lead to paradoxical outcomes. Any pragmatic
method for running a multi-issue election will
have to balance these two concerns. We identify
and analyse the problem of generating an agenda
for a given election, specifying which issues to vote
on together in local elections and in which order to
schedule those local elections
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