Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer Science. This paper aims to chart out the main developments of the field over the last ten years and to take a critical view of these developments from several perspectives: logical, epistemological, computational and suitability to application. The paper attempts to expose some of the challenges and prospects for the further development of the field.

This paper presents a new system called ProLogICA for Abductive Logic Programming (ALP) with Negation as Failure (NAF) and Integrity Constraints (ICs). The system builds upon existing ALP techniques but includes several optimisations and extensions necessitated by recent applications in computational biology, temporal reasoning and machine learning. Unlike some other ALP systems that support non-ground abduction through the integrated use of constraint solving, we adopt a more lightweight approach which avoids this complexity at the expense of only computing ground hypotheses. We argue our approach is suited to a wide class of real-world problems and demonstrate the effectiveness of ProLogICA on three non-trivial applications.

. This paper presents the design and implementation of an aircrew assignment system based on the Artificial Intelligence principles and techniques of abductive reasoning as captured by the framework of Abductive Logic Programming (ALP). The aim of this work was to produce a system for Cyprus Airways that can be used to provide a solution to the airline's crew scheduling problem whose quality was comparable with the manual solutions generated by human experts on this particular problem. In addition to this the system should also constitute a tool with which its operators could continually customize the solutions to new needs and preferences of the company and the crew. The abductive approach (using ALP) adopted in our work offers a flexible modeling environment in which both the problem and its constraints can be easily represented directly from their high-level natural specification. This high-level representation offers two main advantages in the development of an applica...

Abstract. This paper presents a new Abductive Logic Programming (ALP) approach for assisting clinicians in the selection of antiretroviral drugs for patients infected with Human Immunodeficiency Virus (HIV). The approach is comparable to laboratory genotypic resistance testing in that it aims to determine which viral mutations a patient is carrying and predict which drugs they are most likely resistant to. But, instead of genetically analysing samples of the virus taken from patients – which is not always practicable – our approach infers likely mutations using the patient’s full clinical history and a model of drug resistance maintained by a leading HIV research agency. Unlike previous applications of abduction, our approach does not attempt to find the ”best ” explanations, as we can never be absolutely sure which mutations a patient is carrying. Rather, the intrinsic uncertainty of this domain means that multiple alternative explanations are inevitable and we must seek ways to extract useful information from them. The computational and pragmatic issues raised by this approach have led us to develop a new ALP methodology for handling numerous explanations and for drawing predictions with associated levels of confidence. We present our in-Silico Sequencing System (iS3) for reasoning about HIV drug resistance as a concrete example of this approach. 1

Introduction and motivation We live in time of computers and scientific and technological progress but this time is also marked with many attacks on big Internet companies. So with expand of Internet people start to protect information that they exchange through Internet. In the Internet world it is necessary for systems as Internet banking, Internet shopping or e-commerce to secure private information that are transferred via Internet. This necessity leads to design security improvements of existing protocols and to design and implement cryptographic algorithms (for example protocols as L2TP, Microsoft PPTP, IPSec, SSH or algorithms as DES, Blowfish and others). Consider that we have two banks, bank "Alice" and bank "Bob" and these two banks for business purposes need the private cipher for their communication. They need this cipher to do secret bank operation. So they need the secure way, how to arrange the cip