Three-valued completion for abductive logic programs

AbstractIn this paper, we propose a three-valued completion semantics for abductive logic programs, which solves some problems associated with the Console et al. two-valued completion semantics. The semantics is a generalization of Kunen's completion semantics for general logic programs, which is known to correspond very well to a class of effective proof procedures for general logic programs. Secondly, we propose a proof procedure for abductive logic programs, which is a generalization of a proof procedure for general logic programs based on constructive negation. This proof procedure is sound and complete with respect to the proposed semantics. By generalizing a number of results on general logic programs to the class of abductive logic programs, we present further evidence for the idea that limited forms of abduction can be added quite naturally to general logic programs

Multi-agent Confidential Abductive Reasoning

In the context of multi-agent hypothetical reasoning, agents typically have partial knowledge about their environments, and the union of such knowledge is still incomplete to represent the whole world. Thus, given a global query they collaborate with each other to make correct inferences and hypothesis, whilst maintaining global constraints. Most collaborative reasoning systems operate on the assumption that agents can share or communicate any information they have. However, in application domains like multi-agent systems for healthcare or distributed software agents for security policies in coalition networks, confidentiality of knowledge is an additional primary concern. These agents are required to collaborately compute consistent answers for a query whilst preserving their own private information. This paper addresses this issue showing how this dichotomy between "open communication" in collaborative reasoning and protection of confidentiality can be accommodated. We present a general-purpose distributed abductive logic programming system for multi-agent hypothetical reasoning with confidentiality. Specifically, the system computes consistent conditional answers for a query over a set of distributed normal logic programs with possibly unbound domains and arithmetic constraints, preserving the private information within the logic programs. A case study on security policy analysis in distributed coalition networks is described, as an example of many applications of this system

Three-valued completion for abductive logic programs

There is a growing interest in ways to represent incomplete information in logic programs. It has been shown that limited forms abduction can be used quite elegantly for this purpose. In this paper, we propose a a three-valued completion semantics for abductive logic programs, which solves some problems associated with Console et al’s two-valued completion semantics. The semantics is a generalization of Kunen’s completion semantics for general logic programs, which is know to correspond very well to a class of effective proof procedures for general logic programs. Secondly, we propose a proof procedure for abductive logic programs, which is a generalization of a proof procedure for general logic programs based on constructive negation. This proof procedure is sound and complete with respect to the proposed semantics. Basically, by generalizing a number of results on general logic programs to the class of abductive logic programs, we present further evidence for the idea that limited forms of abduction can be added quite naturally to general logic programs. One problem that remains, is the occurrence of inconsistencies. We argue that there are cases in which these do not pose a problem

Distributed Abductive Reasoning: Theory, Implementation and Application

Abductive reasoning is a powerful logic inference mechanism that allows assumptions to be made during answer computation for a query, and thus is suitable for reasoning over incomplete knowledge. Multi-agent hypothetical reasoning is the application of abduction in a distributed setting, where each computational agent has its local knowledge representing partial world and the union of all agents' knowledge is still incomplete. It is different from simple distributed query processing because the assumptions made by the agents must also be consistent with global constraints. Multi-agent hypothetical reasoning has many potential applications, such as collaborative planning and scheduling, distributed diagnosis and cognitive perception. Many of these applications require the representation of arithmetic constraints in their problem specifications as well as constraint satisfaction support during the computation. In addition, some applications may have confidentiality concerns as restrictions on the information that can be exchanged between the agents during their collaboration. Although a limited number of distributed abductive systems have been developed, none of them is generic enough to support the above requirements. In this thesis we develop, in the spirit of Logic Programming, a generic and extensible distributed abductive system that has the potential to target a wide range of distributed problem solving applications. The underlying distributed inference algorithm incorporates constraint satisfaction and allows non-ground conditional answers to be computed. Its soundness and completeness have been proved. The algorithm is customisable in that different inference and coordination strategies (such as goal selection and agent selection strategies) can be adopted while maintaining correctness. A customisation that supports confidentiality during problem solving has been developed, and is used in application domains such as distributed security policy analysis. Finally, for evaluation purposes, a flexible experimental environment has been built for automatically generating different classes of distributed abductive constraint logic programs. This environment has been used to conduct empirical investigation of the performance of the customised system