Constraints, Lazy Constraints, or Propagators in ASP Solving: An Empirical Analysis

Answer Set Programming (ASP) is a well-established declarative paradigm. One of the successes of ASP is the availability of efficient systems. State-of-the-art systems are based on the ground+solve approach. In some applications this approach is infeasible because the grounding of one or few constraints is expensive. In this paper, we systematically compare alternative strategies to avoid the instantiation of problematic constraints, that are based on custom extensions of the solver. Results on real and synthetic benchmarks highlight some strengths and weaknesses of the different strategies. (Under consideration for acceptance in TPLP, ICLP 2017 Special Issue.)Comment: Paper presented at the 33nd International Conference on Logic Programming (ICLP 2017), Melbourne, Australia, August 28 to September 1, 2017. 16 page

Parsing Combinatory Categorial Grammar with Answer Set Programming: Preliminary Report

Combinatory categorial grammar (CCG) is a grammar formalism used for natural language parsing. CCG assigns structured lexical categories to words and uses a small set of combinatory rules to combine these categories to parse a sentence. In this work we propose and implement a new approach to CCG parsing that relies on a prominent knowledge representation formalism, answer set programming (ASP) - a declarative programming paradigm. We formulate the task of CCG parsing as a planning problem and use an ASP computational tool to compute solutions that correspond to valid parses. Compared to other approaches, there is no need to implement a specific parsing algorithm using such a declarative method. Our approach aims at producing all semantically distinct parse trees for a given sentence. From this goal, normalization and efficiency issues arise, and we deal with them by combining and extending existing strategies. We have implemented a CCG parsing tool kit - AspCcgTk - that uses ASP as its main computational means. The C&C supertagger can be used as a preprocessor within AspCcgTk, which allows us to achieve wide-coverage natural language parsing.Comment: 12 pages, 2 figures, Proceedings of the 25th Workshop on Logic Programming (WLP 2011

The EU's Blue Card: will it attract Asia's highly skilled?

As of this year, the EU Council will implement Directive No. 2009/50/EC of 25 May 2009, which is meant to coordinate and simplify the immigration of highly skilled migrants (HSMs) from third countries. It is expected that the new system, providing HSMs with "blue cards", will not only help Europe overcome current shortages of skilled labour but also contribute to alleviating the continent's ageing problem. We argue that this action is overdue, but we maintain that the impact of the measures will be rather small in this decade. Those countries from which a growing inflow of HSMs is expected are increasingly demanding highly qualified personnel themselves or are eager to lure them back. Thus, the EU will need to make additional efforts in order to create a win-win situation for host and home countries as well as for the HSMs themselves. The overdue blue card initiative provides a common starting point for HSMs to jointly consider the majority of European countries as potential host locations. It is doubtful, however, that the blue card will have a significant impact on the pattern of immigration to the European countries before 2020. Past attempts to open up immigration for the highly skilled have been less than successful. A 'green card' initiative by the German government in 2004, which aimed to attract IT personnel from India, provides a useful case study about a rather limited response from Asian HSMs to move to Europe. In addition to the traditional immigration countries’ hunt for HSMs, strong economic growth and dynamic restructuring in emerging economies – particularly China and India - have intensified the global war for talents. They have introduced a reverse brain drain policy, trying to attract highly qualified foreign personnel. Along with the United States and other traditional immigration countries like Canada and Australia, China, in particular, is going to become an important competitor on the international market for the highly skilled

Prolog and ASP Inference Under One Roof

Answer set programming (ASP) is a declarative programming paradigm stemming from logic programming that has been successfully applied in various domains. Despite amazing advancements in ASP solving, many applications still pose a challenge that is commonly referred to as grounding bottleneck. Devising, implementing, and evaluating a method that alleviates this problem for certain application domains is the focus of this paper. The proposed method is based on combining backtracking-based search algorithms employed in answer set solvers with SLDNF resolution from PROLOG. Using PROLOG inference on non-ground portions of a given program, both grounding time and the size of the ground program can be substantially reduced

Combining task and motion planning:challenges and guidelines

Combined Task and Motion Planning (TAMP) is an area where no one-fits-all solution can exist. Many aspects of the domain, as well as operational requirements, have an effect on how algorithms and representations are designed. Frequently, trade-offs have to be made to build a system that is effective. We propose five research questions that we believe need to be answered to solve real-world problems that involve combined TAMP. We show which decisions and trade-offs should be made with respect to these research questions, and illustrate these on examples of existing application domains. By doing so, this article aims to provide a guideline for designing combined TAMP solutions that are adequate and effective in the target scenario