Possibilistic logic is a logic of uncertainty tailored for reasoning under incomplete evidence and partially inconsistent knowledge. At the syntactic level it handles formulas of propositional or… Expand

This article characterize the exact number of candidates for which manipulation becomes hard for the plurality, Borda, STV, Copeland, maximin, veto, plurality with runoff, regular cup, and randomized cup protocols and shows that for simpler manipulation problems, manipulation cannot be hard with few candidates.Expand

A survey of some of the most salient issues in Multiagent Resource Allocation, including various languages to represent the pref-erences of agents over alternative allocations of resources as well as different measures of social welfare to assess the overall quality of an allocation.Expand

It is shown that the possible and necessary Condorcet winners for a partial preference profile can be computed in polynomial time as well and point out connections to vote manipulation and elicitation.Expand

This new approach leads to a nonmonotonic inference which satisfies the "rationality" property while solving the problem of blocking of property inheritance and differs from and improves previous equivalent approaches such as Gardenfors and Makinson's expectation-based inference, Pearl's System Z and possibilistic logic.Expand

This work generalizes the framework of Boolean games to n-players games which are not necessarily zero-sum, gives simple characterizations of Nash equilibria and dominated strategies, and investigates the computational complexity of the related problems.Expand

It is shown here that both dominance and consistency testing for general CP-nets are PSPACE-complete, and the reductions used in the proofs are from STRIPS planning, and thus establish strong connections between both areas.Expand

We introduce the notion of combinatorial vote, where a group of agents (or voters) is supposed to express preferences and come to a common decision concerning a set of non-independent variables to… Expand

We propose a framework for dealing with probabilistic uncertainty in constraint satisfaction problems, associating with each constraint the probability that it is a part of the real problem (the… Expand