Knowledge Representation for High-Level Norms and Violation Inference in Logic Programming

Most of the knowledge Representation formalisms developed for representing prescriptive norms can be categorized as either suitable for representing either low level or high level norms.We argue that low level norm representations do not advance the cause of autonomy in agents in the sense that it is not the agent itself that determines the normative position it should be at a particular time, on the account of a more general rule. In other words an agent on some external system for a nitty gritty prescriptions of its obligations and prohibitions. On the other hand, high level norms which have an explicit description of a norm's precondition and have some form of implication, do not as they exist in the literature do not support generalized inferences about violation like low level norm representations do. This paper presents a logical formalism for the representation of high level norms in open societies that enable violation inferences that detail the situation in which the norm violation took place and the identity of the norm violation. Norms are formalized as logic programs whose heads specify what an agent is obliged or permitted to do when a situation arises and within what time constraint of the situation.Each norm is also assigned an identity using some reification scheme. The body of each logic program describes the nature of the situation in which the agent is expected to act or desist from acting. This kind of violation is novel in the literature.