This paper reports on the Second Answer Set Programming Competition . The competitions in areas of Satisfiability checking, Pseudo-Boolean constraint solving and Quantified Boolean Formula evaluation have proven to be a strong driving force for a community to develop better performing systems. Following this experience, the Answer Set Programming competition series was set up in 2007, and ran as part of the International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR). This second competition, held in conjunction with LPNMR 2009, differed from the first one in two important ways. First, while the original competition was restricted to systems designed for the answer set programming language , the sequel was open to systems designed for other modeling languages, as well. Consequently, among the contestants of the second competition were a CLP(FD) team and three model generation systems for (extensions of) classical logic. Second, this latest competition covered not only satisfiability problems but also optimization ones. We present and discuss the set-up and the results of the competition.

The Second Answer Set Programming Competition

Agent-based collaborative product design engineering: an industrial case study

The use of adhesive bonding in joining of materials with different characteristics is of major importance in a variety of microelectronic and photonic applications. The curing of such adhesives is also of great consequence, with the use of optical radiation for adhesive curing becoming the method of choice in various applications, especially bonding of components in microelectronics and fiber–optic assembly. This article reviews recent advances in the development of adhesives, their applications, and their curing methods using optical radiation; it also includes a brief overview of the adhesion mechanisms.

Adhesive bonding in microelectronics and photonics

Testing and fault localization are very expensive software engineering tasks that have been tried to be automated. Although many successful techniques have been designed, the actual change of the code for fixing the discovered faults is still a human-only task. Even in the ideal case in which automated tools could tell us exactly where the location of a fault is, it is not always trivial how to fix the code. In this paper we analyse the possibility of automating the complex task of fixing faults. We propose to model this task as a search problem, and hence to use for example evolutionary algorithms to solve it. We then discuss the potential of this approach and how its current limitations can be addressed in the future. This task is extremely challenging and mainly unexplored in the literature. Hence, this paper only covers an initial investigation and gives directions for future work. A research prototype called JAFF and a case study are presented to give first validation of this approach.

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S. Abbas

Papers

Proceedings of the Sixth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems

Representing design information and safety constraints