Christoph Redl

The Fourth Answer Set Programming Competition: Preliminary Report

Answer Set Programming is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, PDDL and many others. Since its first informal editions, ASP systems are compared in the nowadays customary ASP Competition. The fourth ASP Competition, held in 2012/2013, is the sequel to previous editions and it was jointly organized by University of Calabria Italy and the Vienna University of Technology Austria. Participants competed on a selected collection of benchmark problems, taken from a variety of research areas and real world applications. The Competition featured two tracks: the Model& Solve Track, held on an open problem encoding, on an open language basis, and open to any kind of system based on a declarative specification paradigm; and the System Track, held on the basis of fixed, public problem encodings, written in a standard ASP language.

Automatic SLA Matching and Provider Selection in Grid and Cloud Computing Markets

Cloud computing is a novel computing paradigm that offers data, software, and hardware services in a manner similar to traditional utilities such as water, electricity, and telephony. Usually, in Cloud and Grid computing, contracts between traders are established using Service Level Agreements (SLAs), which include objectives of service usage. However, due to the rapidly growing number of service offerings and the lack of a standard for their specification, manual service selection is a costly task, preventing the successful implementation of ubiquitous computing on demand. In order to counteract these issues, automatic methods for matching SLAs are necessary. In this paper, we introduce a method for finding semantically equal SLA elements from differing SLAs by utilizing several machine learning algorithms. Moreover, we utilize this method to enable automatic selection of optimal service offerings for Cloud and Grid users. Finally, we introduce a framework for automatic SLA management, present a simulation-based evaluation, and demonstrate several significant benefits of our approach for Cloud and Grid users.

Conflict-driven asp solving with external sources

Answer Set Programming (ASP) is a well-known problem solving approach based on nonmonotonic logic programs and efficient solvers. To enable access to external information, HEX-programs extend programs with external atoms, which allow for a bidirectional communication between the logic program and external sources of computation (e.g., description logic reasoners and Web resources). Current solvers evaluate HEX-programs by a translation to ASP itself, in which values of external atoms are guessed and verified after the ordinary answer set computation. This elegant approach does not scale with the number of external accesses in general, in particular in presence of nondeterminism (which is instrumental for ASP). In this paper, we present a novel, native algorithm for evaluating HEX-programs which uses learning techniques. In particular, we extend conflict-driven ASP solving techniques, which prevent the solver from running into the same conflict again, from ordinary to HEX-programs. We show how to gain additional knowledge from external source evaluations and how to use it in a conflict-driven algorithm. We first target the uninformed case, i.e., when we have no extra information on external sources, and then extend our approach to the case where additional meta-information is available. Experiments show that learning from external sources can significantly decrease both the runtime and the number of considered candidate compatible sets.

A model building framework for Answer Set Programming with external computations

As software systems are getting increasingly connected, there is a need for equipping nonmonotonic logic programs with access to external sources that are possibly remote and may contain information in heterogeneous formats. To cater for this need, HEX programs were designed as a generalization of answer set programs with an API style interface that allows to access arbitrary external sources, providing great flexibility. Efficient evaluation of such programs however is challenging, and it requires to interleave external computation and model building; to decide when to switch between these tasks is difficult, and existing approaches have limited scalability in many real-world application scenarios. We present a new approach for the evaluation of logic programs with external source access, which is based on a configurable framework for dividing the non-ground program into possibly overlapping smaller parts called evaluation units. The latter will be processed by interleaving external evaluation and model building using an evaluation graph and a model graph, respectively, and by combining intermediate results. Experiments with our prototype implementation show a significant improvement compared to previous approaches. While designed for HEX-programs, the new evaluation approach may be deployed to related rule-based formalisms as well.

Efficient HEX-program evaluation based on unfounded sets

HEX-programs extend logic programs under the answer set semantics with external computations through external atoms. As reasoning from ground Horn programs with nonmonotonic external atoms of polynomial complexity is already on the second level of the polynomial hierarchy, minimality checking of answer set candidates needs special attention. To this end, we present an approach based on unfounded sets as a generalization of related techniques for ASP programs. The unfounded set detection is expressed as a propositional SAT problem, for which we provide two different encodings and optimizations to them. We then integrate our approach into a previously developed evaluation framework for HEX-programs, which is enriched by additional learning techniques that aim at avoiding the reconstruction of the same or related unfounded sets. Furthermore, we provide a syntactic criterion that allows one to skip the minimality check in many cases. An experimental evaluation shows that the new approach significantly decreases runtime.

Domain expansion for ASP-programs with external sources

Answer set programming (ASP) is a popular approach to declarative problem solving which for broader usability has been equipped with external source access. The latter may introduce new constants to the program (known as value invention), which can lead to infinite answer sets and non-termination; to prevent this, syntactic safety conditions on programs are common which considerably limit expressiveness (in particular, recursion). We present liberal domain-expansion (lde) safe programs, a novel generic class of ASP programs with external source access and value invention that enjoy finite restrictability, i.e., equivalence to a finite ground version. They use term bounding functions as a parametric notion of safety, which can be instantiated with syntactic, semantic or combined safety criteria; this empowers us to generalize and integrate many other notions of safety from the literature, and modular composition of criteria makes future extensions easy. Furthermore, we devise a grounding algorithm for lde-safe programs which in contrast to traditional algorithms can ground any such program directly without the need for program decomposition. While we present our approach on top of a proposed formalism in order to make the formalization precise, the general concepts carry over to related formalisms and important special cases as well. An experimental evaluation of lde-safety on various applications confirms the practicability of our approach.

ActHEX: Implementing HEX Programs with Action Atoms

acthex programs are a convenient tool for connecting stateful external environments to logic programs. In the acthex framework, actual actions on an external environment can be declaratively selected, rearranged, scheduled and then executed depending on intelligence specified in an ASP-based language. We report in this paper about recent improvements of the formal and of the operational acthex programming framework. Besides yielding a significant increase in versatility of the framework, we also present illustrative application showcases and a short evaluation thereof exhibiting computational acthex strengths.

The dlvhex system for knowledge representation: recent advances (system description)

The DLVHEX system implements the HEX-semantics, which integrates answer set programming (ASP) with arbitrary external sources. Since its first release ten years ago, significant advancements were achieved. Most importantly, the exploitation of properties of external sources led to efficiency improvements and flexibility enhancements of the language, and technical improvements on the system side increased users convenience. In this paper, we present the current status of the system and point out the most important recent enhancements over early versions. While existing literature focuses on theoretical aspects and specific components, a birds eye view of the overall system is missing. In order to promote the system for real-world applications, we further present applications which were already successfully realized on top of DLVHEX. This paper is under consideration for acceptance in Theory and Practice of Logic Programming.

Angry-HEX: An Artificial Player for Angry Birds Based on Declarative Knowledge Bases

This paper presents the Angry-HEX artificial intelligent agent that participated in the 2013 and 2014 Angry Birds Artificial Intelligence Competitions. The agent has been developed in the context of a joint project between the University of Calabria (UniCal) and the Vienna University of Technology (TU Vienna). The specific issues that arise when introducing artificial intelligence in a physics-based game are dealt with a combination of traditional imperative programming and declarative programming, used for modeling discrete knowledge about the game and the current situation. In particular, we make use of HEX programs, which are an extension of answer set programming (ASP) programs toward integration of external computation sources, such as 2-D physics simulation tools.

HEX-Programs with Nested Program Calls

Answer-Set Programming (ASP) is an established declarative programming paradigm. However, classical ASP lacks subprogram calls as in procedural programming, and access to external computations (akin to remote procedure calls) in general. This feature is desired for increasing modularity and—assuming proper access in place—(meta-)reasoning over subprogram results. While hex-programs extend classical ASP with external source access, they do not support calls of (sub-)programs upfront. We present nested hex -programs, which extend hex-programs to serve the desired feature in a user-friendly manner. Notably, the answer sets of called sub-programs can be individually accessed. This is particularly useful for applications that need to reason over answer sets like belief set merging, user-defined aggregate functions, or preferences of answer sets. We will further present a novel method for rapid prototyping of external sources by the use of nested programs.