Box 1738 3000 DR Rotterdam, the Netherlands YTANQFAC.FBK.EUR..NL Abstract Deontic logic, the logic of obligations and permissions, is plagued by several paradoxes that have to be understood before deontic logic can be used as a knowledge representation language. In this paper we extend the temporal analysis of Chishohn's paradox using a deontic logic that combines temporal and preferential notions. Introduction Deontic logic is a modal logic in which Op is read as'p ought to be (done).' Deontic logic has traditionally been used by philosophers to analyze the structure of the normative use of language. In the eighties deontic logic had a revival, when it was discovered by computer scientists that this logic can be used for the formal specification and validation of a wide variety of topics in computer science (for an overview and further references see (Wieringa & Meyer 1993)). The advantage is that norms can be violated without creating an inconsistency in the formal specification, in contrast to violations of hard constraints. Another application is the use of deontic logic to represent legal reasoning in legal expert systems in artificial intelligence. Legal expert systems have to be able to reason about legal rules and documents such as for example a trade contract.
In this paper we introduce an abstract theory of normative reasoning, whose central notion is the generation of obligations, permissions and institutional facts from conditional norms. We present various semantics and their proof systems. The theory can be used to classify and compare new candidates for standards of normative reasoning, and to explore more elaborate forms of normative reasoning than studied thus far.
Aggregative deontic detachment is a new form of deontic detachment that keeps track of previously detached obligations. We argue that it handles iteration of successive detachments in a more principled manner than the traditional systems do. To study this new form of deontic detachment, we introduce a 'minimal' logic for aggregative deontic detachment, and we discuss various properties of the logic.
The area of formal ethics is experiencing a shift from a unique or standard approach to normative reasoning, as exemplified by so-called standard deontic logic, to a variety of application-specific theories. However, the adequate handling of normative concepts such as obligation, permission, prohibition, and moral commitment is challenging, as illustrated by the notorious paradoxes of deontic logic. In this article we introduce an approach to design and evaluate theories of normative reasoning. In particular, we present a formal framework based on higher-order logic, a design methodology, and we discuss tool support. Moreover, we illustrate the approach using an example of an implementation, we demonstrate different ways of using it, and we discuss how the design of normative theories is now made accessible to non-specialist users and developers.
We explore the notions of permission and obligation and their role in knowledge representation, especially as guides to action for planning systems. We first present a simple conditional deontic logic (or more accurately a preference logic) of the type common in the literature and demonstrate its equivalence to a number of modal and conditional systems for default reasoning. We show how the techniques of conditional default reasoning can be used to derive factual preferences from conditional preferences. We extend the system to account for the effect of beliefs on an agent's obligations, including beliefs held by default. This leads us to the notion of a conditional goal, goals toward which an agent should strive according to its belief state. We then extend the system (somewhat naively) to model the ability of an agent to perform actions. Even with this simple account, we are able to show that the deontic slogan "make the best of a bad situation" gives rise to several interpretations or strategies for determining goals (and actions). We show that an agent can improve its decisions and focus its goals by making observations, or increasing its knowledge of the world. Finally, we discuss how this model might be extended and used in the planning process, especially to represent planning under uncertainty in a qualitative manner.