Inductive Logic Programming as Abductive Search

We present a novel approach to non-monotonic ILP and its implementation called TAL (Top-directed Abductive Learning). TAL overcomes some of the completeness problems of ILP systems based on Inverse Entailment and is the first top-down ILP system that allows background theories and hypotheses to be normal logic programs. The approach relies on mapping an ILP problem into an equivalent ALP one. This enables the use of established ALP proof procedures and the specification of richer language bias with integrity constraints. The mapping provides a principled search space for an ILP problem, over which an abductive search is used to compute inductive solutions

characterization of a polylactic acid pla produced by fused deposition modeling fdm technology

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development and calibration of a cfd based model of the bed fusion slm additive manufacturing process aimed at optimising laser parameters

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Austenitic stainless steels manufacturing by laser powder bed fusion technique

In this paper we report about the possibility to process stainless steels by laser powder bed fusion (L-PBF) systems. Austenitic stainless steels are analysed showing the possibility to successfully process them, targeting different applications. In particular, it is shown that stainless steels can be successfully processed and their mechanical behaviour allow them to be put in service. Porosities inside manufactured components are extremely low and comparable to conventionally processed materials. Mechanical performances are even higher than standard requirements. Micro surface roughness typical of the as-built material can act as crack initiator, reducing the strength in both quasi-static and dynamic conditions

Usage analytics: a process to extract and analyse usage data to understand user behaviour in cloud

Usage in the software field deals with knowledge about how end-users use the application and how the application responds to the users’ action. Understanding usage data can help developers optimise the application development process by prioritising the resources such as time, cost and man power on features of the application which are critical for the user. However, in a complex cloud computing environment, the process of extracting and analysing usage data is difficult since the usage data is spread across various front-end interfaces and back-end underlying infrastructural components of the cloud that host the application and are of different types and formats. In this paper, we propose usage analytics, a process to extract and analyse usage to understand the behavioural usage patterns of the user with the aim to identify features critical to user. We demonstrate how to identify the features in a cloud based application, how to extract and analyse the usage data to understand the user behaviour

Nonmonotonic Inductive Logic Programming as Abductive Search

Inductive Logic Programming (ILP) is a machine learning technique that relies on logic programs as a representation language. Most of the effort in the field of ILP has concentrated on a restricted class of problems, providing solutions that do not fully support negation. On the other hand, integration of negation and nonmonotonic reasoning in logic programming is common and important for a number of problems. This thesis presents an approach to nonmonotonic ILP that is based on a transformation of the original problem to a problem that can be solved by employing abductive reasoning. In particular we present a general framework for the transformation that can be used as reference for concrete implementations. We instantiate the transformation to derive two alternative implementations that are rooted in the two dominant computational logic paradigms: Prolog and Answer Set Programming (ASP). In the first case, we derive an implementation, called TAL, that is based on the abductive proof procedure SLDNFA and uses a customisable best-first search on the space of abductive solutions. In the second case the transformation is further refined in order to exploit the computational properties of available ASP solvers. In the proposed system called ASPAL, a theory is constructed from a set of mode declarations and used to extend the search of the underlying solver, so enabling the derivation of inductive hypotheses. We provide completeness and soundness results for the framework and the ILP systems presented and show how, as a consequence of this, it is possible to induce complex multi-predicate hypotheses involving negation, recursion and the definition of elements of the domain that are not directly observed. We validate the framework on established ILP benchmark problems, on some nonmonotonic ILP problems proposed in the literature. Furthermore we demonstrate the approach on a novel application of nonmonotonic ILP to the revision of normative frameworks

Considerazioni comparatistiche sui limiti dell’arbitrabilità nel falimentto = Comparative considerations on the limits of arbitrability in insolvency proceedings

Examina as soluções na Inglaterra, Estados Unidos e França em comparação com as italianas sobre os conflitos entre o procedimento ordinário de insolvência e natureza privada da arbitragem