What You should Believe

in Proceedings of The 19th Belgian-Dutch Conference on Artificial Intelligence (BNAIC 2007) (2007)

Ten Philosophical Problems in Deontic Logic

in Normative Multi-agent Systems (2007)

The paper discusses ten philosophical problems in deontic logic: how to formally represent norms, when a set of norms may be termed `coherent', how to deal with normative conflicts, how contrary-to-duty ... [more ▼]

The paper discusses ten philosophical problems in deontic logic: how to formally represent norms, when a set of norms may be termed `coherent', how to deal with normative conflicts, how contrary-to-duty obligations can be appropriately modeled, how dyadic deontic operators may be redefined to relate to sets of norms instead of preference relations between possible worlds, how various concepts of permission can be accommodated, how meaning postulates and counts-as conditionals can be taken into account, and how sets of norms may be revised and merged. The problems are discussed from the viewpoint of input/output logic as developed by van der Torre Makinson. We argue that norms, not ideality, should take the central position in deontic semantics, and that a semantics that represents norms, as input/output logic does, provides helpful tools for analyzing, clarifying and solving the problems of deontic logic. [less ▲]

Aggregation in Multi-Agent Systems and the Problem of Truth-Tracking

Poster (2007)

One of the major problems that artificial intelligence needs to tackle is the combination of different and potentially conflicting sources of information. Examples are multi-sensor fusion, database ... [more ▼]

One of the major problems that artificial intelligence needs to tackle is the combination of different and potentially conflicting sources of information. Examples are multi-sensor fusion, database integration and expert systems development. In this paper we are interested in the aggregation of propositional logic-based information, a problem recently addressed in the literature on information fusion. It has applications in multiagent systems that aim at aggregating the distributed agent-based knowledge into an (ideally) unique set of propositions. We consider a group of autonomous agents who individually hold a logically consistent set of propositions. Each set of propositions represents an agent's beliefs on issues on which the group has to make a collective decision. To make the collective decision, several aggregation procedures have been proposed in the literature. Assuming that all propositions in question are factually right or wrong, we ask how good belief fusion is as a truth tracker. Will it single out the true set of propositions? And how does information fusion compare with other aggregation procedures? We address these questions in a probabilistic framework and show that information fusion does especially well for agents with a middling competence of hitting the truth of an individual proposition. [less ▲]

Belief revision, belief merging and voting

in Proceedings of the Seventh Conference on Logic and the Foundations of Games and Decision Theory (LOFT06) (2006)

In belief revision, an agent is faced with the problem of choosing between several alternatives when trying to restore con- sistency to theory. Ideally, the choice process is conducted in a way that ... [more ▼]

In belief revision, an agent is faced with the problem of choosing between several alternatives when trying to restore con- sistency to theory. Ideally, the choice process is conducted in a way that verifies a number of fairness principles. On the other hand, be- lief merging concerns with the problem of determining a group’s be- liefs from individual members’ beliefs that are not always compatible with each other. Similarly, in voting systems, a social welfare func- tion takes individual preferences into account in order to produce a collective preference. Here again certain fairness principles are desir- able. In this paper, we investigate the relationship between revision, merging and voting. [less ▲]