. In this paper we propose the deontic logic dus, that formalizes reasoning about prescriptive obligations in update semantics. In dus the definition of logical validity of obligations is not based on truth values but on action dynamics. You know the meaning of a normative sentence if you know the change it brings about in the ideality relation of anyone the news conveyed by the norm applies to. 1 The logic of norms One of the first topics discussed in the development of deontic logic was the question whether norms have truth values. For example, Von Wright (1981, 1998) was hesitant to call deontic formulas `logical truths,' because "it seems to be a matter of extralogical decision when we shall say that `there are' or `are not' such and such norms." Alchourr'on and Bulygin discussed the possibility of a logic of norms, which they distinguish from the logic of normative propositions. "One such issue is the problem of the possibility of a logic of norms. Some authors think that there ...

We consider the two-fold problem of representing collective beliefs and aggregating these beliefs.

. Intelligent agents have to be able to merge inputs received from different sources in a coherent and rational way. Recently, several proposals have been made for the merging of structures in which it is possible to encode the preferences of sources [5, 4, 12--14, 1]. Information merging has much in common with the goals of social choice theory: to define operations reflecting the preferences of a society from the individual preferences of the members of the society. Given this connection it seems reasonable to require that any framework for the merging of information has to provide satisfactory ways of dealing with the problems raised in social choice theory. In this paper we investigate the link between the merging of epistemic states and two important results in social choice theory. We show that Arrow's well-known impossibility theorem [2] can be circumvented when the preferences of sources are represented in terms of epistemic states. This is achieved by providing a consistent set of properties for merging from which Arrow-like properties can be derived. We extend this to a consistent framework which includes properties corresponding to the notion of being strategy-proof. The existence of such an extended framework can be seen as a circumvention of the impossibility result of Gibbard and Satterthwaite [8, 17, 18] and related results [6, 3]. 1

preference description language PDL . This language allows us to combine qualitative and quantitative, penalty based preferences in a flexible way. This makes it possible to express complex preferences which are needed in many realistic optimization settings. We show that several preference handling methods described in the literature are special cases of our approach. We also demonstrate that PDL expressions can be compiled to logic programs which can be used as tester programs in a generate-and-improve method for finding optimal answer sets.

Abstract. Extended Feature Oriented Domain Analysis (FODA) Feature Diagrams (EFD) were introduced to compensate for a purported ambiguity and lack of precision and expressiveness of the original FODA feature diagrams (OFD). However, EFD never received a formal semantics, which is the hallmark of precision and unambiguity. We propose here a semantics for both diagrams. From this we demonstrate that OFD are precise, unambiguous, and expressively complete, and thus that all extensions add no expressiveness. A finer notion is thus needed to compare these languages. Two solutions are well-established: succinctness and embeddability, that measures naturalness of a language. This tool shows that EFD indeed bring some naturalness, but are harmfully redundant and that the same naturalness can be attained with the simpler varied FD (VFD). We also show that no ambiguity is present, in fact.

Some recent research suggests that it is useful to conduct information merging on the level of epistemic states as an alternative to the usual approach of knowledge base merging [Benferhat et al., 1999; 2000; Meyer, 2000] . One way in which to represent epistemic states syntactically is in terms of ranked knowledge bases. We discuss compact representations of ranked knowledge bases and provide a uniform method for obtaining syntactic representations of a large class of semantic merging operations which is linear in n times the product of the sizes of the n ranked knowledge bases to be merged. We show that the structure of some semantic merging operations can be exploited to provide methods for obtaining syntactic representations which are linear in the sum of the sizes of the n ranked knowledge bases to be merged. For others, the general method represents the best we can do in terms of computational complexity. 1

We define preference in terms of priority sequences, a concept which is initially from optimality theory. In case agents only have incomplete information, beliefs are introduced. We propose three definitions to describe three different procedures agents may take to obtain preference from the incomplete information. Changes of preference are explored w.r.t their sources: changes of priority sequence, and changes in beliefs. We extend the results to the many agent case. Among other things this gives a new view on cooperation. 1

Abstract. This paper briefly considers several research issues, some of which are on-going and some others are for further research. The starting point is that many AI topics, especially those related to the EC-SQARU and KR conferences, can bring a lot to the representation and the resolution of social choice problems. I surely do not claim to make an exhaustive list of problems, but I rather list some problems that I find important, give some relevant references and point out some potential research issues 1. 1

Intelligent agents have to be able to merge inputs received from different sources in a coherent and rational way. Several proposals have been made for the merging of structures in which it is possible to encode the preferences of sources [5, 4, 12, 16, 17, 1]. Information merging has much in common with the goals of social choice theory: to define operations reflecting the preferences of a society from the individual preferences of the members of the society. Given this connection it seems reasonable to require that any framework for the merging of information provide satisfactory ways of dealing with the problems raised in social choice theory. We investigate the link between the merging of epistemic states and two important results in social choice theory. We show that Arrow's well-known impossibility theorem [2] can be circumvented when the preferences of sources are represented in terms of epistemic states. This is achieved by providing a consistent set of properties for merging from which Arrow-like properties can be derived. We extend this to a consistent framework which includes properties corresponding to the notion of being strategy-proof. The existence of such an extended framework can be seen as a circumvention of the impossibility result of Gibbard and Satterthwaite [8, 21, 22] and related results [6, 3].

This paper proposes a method allowing an agent to perform in a socially fair way by considering other agents' preferences. Such a balanced action selection process is based on declarative diagnosis, which enables the removal of contradictions arising as all agents' preferences are confronted within the deciding agent. Agents can be negatively affected when some of their preferences are not respected for the sake of a global compromise. The set of preferences to be yielded by agents in order to remove all contradictions in a balanced way (i.e.