Learning Weak Constraints in Answer Set Programming

This paper contributes to the area of inductive logic programming by presenting a new learning framework that allows the learning of weak constraints in Answer Set Programming (ASP). The framework, called Learning from Ordered Answer Sets, generalises our previous work on learning ASP programs without weak constraints, by considering a new notion of examples as ordered pairs of partial answer sets that exemplify which answer sets of a learned hypothesis (together with a given background knowledge) are preferred to others. In this new learning task inductive solutions are searched within a hypothesis space of normal rules, choice rules, and hard and weak constraints. We propose a new algorithm, ILASP2, which is sound and complete with respect to our new learning framework. We investigate its applicability to learning preferences in an interview scheduling problem and also demonstrate that when restricted to the task of learning ASP programs without weak constraints, ILASP2 can be much more efficient than our previously proposed system.Comment: To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 201

Inductive learning of answer set programs

The goal of Inductive Logic Programming (ILP) is to find a hypothesis that explains a set of examples in the context of some pre-existing background knowledge. Until recently, most research on ILP targeted learning definite logic programs. This thesis constitutes the first comprehensive work on learning answer set programs, introducing new learning frameworks, theoretical results on the complexity and generality of these frameworks, algorithms for learning ASP programs, and an extensive evaluation of these algorithms. Although there is previous work on learning ASP programs, existing learning frameworks are either brave -- where examples should be explained by at least one answer set -- or cautious where examples should be explained by all answer sets. There are cases where brave induction is too weak and cautious induction is too strong. Our proposed frameworks combine brave and cautious learning and can learn ASP programs containing choice rules and constraints. Many applications of ASP use weak constraints to express a preference ordering over the answer sets of a program. Learning weak constraints corresponds to preference learning, which we achieve by introducing ordering examples. We then explore the generality of our frameworks, investigating what it means for a framework to be general enough to distinguish one hypothesis from another. We show that our frameworks are more general than both brave and cautious induction. We also present a new family of algorithms, called ILASP (Inductive Learning of Answer Set Programs), which we prove to be sound and complete. This work concerns learning from both non-noisy and noisy examples. In the latter case, ILASP returns a hypothesis that maximises the coverage of examples while minimising the length of the hypothesis. In our evaluation, we show that ILASP scales to tasks with large numbers of examples finding accurate hypotheses even in the presence of high proportions of noisy examples.Open Acces

Standardization In The Home Building Industry: An Empirical Investigation Into The Compatibility Between Accounting And Estimating Cost Codes

The purpose of this study was to investigate the utilization of standardized cost codes for the estimating and accounting functions related to the scale of operations by Pennsylvania’s home building contractors.  Firm size was examined as to its impact on three issues in construction standardization practice:  1) the use of a standardized number system for estimating, 2) the use of a standardized number system for accounting, and 3) the use of the same standardized number system for both estimating and accounting.  Significant differences existed among firm sizes regarding all three items relating to standardized cost codes - a standardized numbering system used for estimating, a standardized numbering system used for accounting, and the same standardized numbering system used for both estimating and accounting functions.  Overall, however, a large percentage of Pennsylvania home building firms are behind the curve with regard to their knowledge and utilization of standardized cost codes

A Theoretical Model For Accounting For Cost Variance In The Residential Home Building Industry

The purpose of this study was to propose a theoretical model for home building contractors. The theoretical framework proposed was formulated from a systems approach focusing on the principles of general systems theory and applying the theory of single-loop learning to the task of a real-time cost variance calculation. In creating the model, the researcher first looked at the concept of general systems theory, applying the system concept using a systems approach. This approach has led to the development of the theoretical model for the home building industry. In the center of the model is the cost variance system interacting with the individual subsystems; estimating, accounting, standards, and technology. This model outlines the importance of four separate subsystems and their interrelationships in the calculation of cost variance. The model in this study has led to several important implications and recommendations for the home building industr

The Utilization Of Accounting Cost Controls In Conjunction With Information Technology In The Home Building Arena

This article examines how cost controls are emphasized and utilized in conjunction with information technology in the home building business by Pennsylvania’s contractors.  The results of the analysis showed significant differences existed in the implementation of cost controls; the periodic use of cost variance; adjustments made based on cost variance feedback; the use of past projects to prepare estimates on future projects, and the use of information technology between and among firms when examined by firm size.  The outcome of the study has led to several important implications for the home building industry