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10:15-10:45Coffee Break
10:50-12:10 Session 67: Propositional Satisfiability
Location: MB, Hörsaal 12
Optimal Neighborhood Preserving Visualization by Maximum Satisfiability
SPEAKER: Jeremias Berg

ABSTRACT. We present a novel approach to low-dimensional neighbor embedding for visualization, based on formulating an information retrieval based neighborhood preservation cost function as Maximum satisfiability on a discretized output display. The method has a rigorous interpretation as optimal visualization based on the cost function. Unlike previous low-dimensional neighbor embedding methods, our formulation is guaranteed to yield globally optimal visualizations, and does so reasonably fast. Unlike previous manifold learning methods yielding global optima of their cost functions, our cost function and method are designed for low-dimensional visualization where evaluation and minimization of visualization errors are crucial. Our method performs well in experiments, yielding clean embeddings of datasets where a state-of-the-art comparison method yields poor arrangements. In a real-world case study for semi-supervised WLAN signal mapping in buildings we outperform state-of-the-art methods.

This work will appear in the proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI 2014).

Maximal Falsifiability: Definitions, Algorithms, and Applications

ABSTRACT. Similarly to Maximum Satisfiability (MaxSAT), Minimum Satisfiability (MinSAT) is an optimization extension of the Boolean Satisfiability (SAT) decision problem. In recent years, both problems have been studied in terms of exact and approximation algorithms. In addition, the MaxSAT problem has been characterized in terms of Maximal Satisfiable Subsets (MSSes) and Minimal Correction Subsets (MCSes), as well as Minimal Unsatisfiable Subsets (MUSes) and minimal hitting set dualization. However, and in contrast with MaxSAT, no such characterizations exist for MinSAT. This paper addresses this issue by casting the MinSAT problem in a more general framework. The paper studies Maximal Falsifiability, the problem of computing a subset-maximal set of clauses that can be simultaneously falsified, and shows that MinSAT corresponds to the complement of a largest subset-maximal set of simultaneously falsifiable clauses, i.e. the solution of the Maximum Falsifiability (MaxFalse) problem. Additional contributions of the paper include novel algorithms for Maximum and Maximal Falsifiability, as well as minimal hitting set dualization results for the MaxFalse problem. Moreover, the proposed algorithms are validated on practical instances.

Latin Squares with Graph Properties
SPEAKER: Hans Zantema

ABSTRACT. In a Latin square of size n every number from 1 to n occurs exactly once in every row and every column. Two neighbors (straight or diagonal) in a Latin square are connected by an edge if their values differ at most 1. We investigate Latin squares for which this underlying graph has typical graph properties, like being connected, being a tree or being Hamiltonian. Searching for such Latin squares shows up combinatorial explosion. Nevertheless, by exploiting current SAT/SMT solving, we explicitly find instances for several variants, or prove that they do not exist.

12:10-13:00 Session 72: Answer Set Programming
Location: MB, Hörsaal 12
Efficient Computation of the Well-Founded Semantics over Big Data

ABSTRACT. Data originating from the Web, sensor readings and social media result in increasingly huge datasets. The so called Big Data comes with new scientific and technological challenges while creating new opportunities, hence the increasing interest in academia and industry. Traditionally, logic programming has focused on complex knowledge structures/programs, so the question arises whether and how it can work in the face of Big Data. In this paper, we examine how the well-founded semantics can process huge amounts of data through mass parallelization. More specifically, we propose and evaluate a parallel approach using the MapReduce framework. Our experimental results indicate that our approach is scalable and that well-founded semantics can be applied to billions of facts. To the best of our knowledge, this is the first work that addresses large scale nonmonotonic reasoning without the restriction of stratification for predicates of arbitrary arity.

Declarative Specification of Benchmark Sessions via ASP
SPEAKER: unknown

ABSTRACT. As a matter of fact, benchmark sessions are easy to describe in a declarative fashion, but are usually painful to implement in practice. In this paper we describe DecBench, a suite of tools conceived for easing the task of configuring and running structured software benchmark analyses of command line executables. Benchmark sessions are specified in DecBench by means of Answer Set Programming (ASP), a declarative knowledge representation language having its roots in nonmonotonic reasoning and logic programming. The provided declarative specification is fed in an ASP solver, and the output is used to produce a Makefile that controls the execution of the specified benchmark analysis. The paper reports also a complete usecase conceived to validate the presented tool.

13:00-14:30Lunch Break
14:30-16:00 Session 75BA: Planning & Scheduling
Location: MB, Hörsaal 12
A Systematic Analysis of Levels of Integration between High-Level Task Planning and Low-Level Feasibility Checks
SPEAKER: unknown

ABSTRACT. We provide a systematic analysis of levels of integration between discrete high-level reasoning and continuous low-level feasibility checks to address hybrid planning problems in robotic applications. We identify four distinct strategies for such an integration: (i) low-level checks are done for all possible cases in advance and then this information is used during plan generation; (ii) low-level checks are done exactly when they are needed during the search for a plan; (iii) low-level checks are done after a plan is computed, and then a new plan is computed if the plan is found infeasible; (iv) similar to the previous strategy of replanning but a new plan is computed subject to the constraints obtained from previous low-level checks. We perform experiments on hybrid planning problems in housekeeping domain considering these four methods of integration, as well as some of their combinations. We analyze the usefulness of different levels of integration in this domain, both from the point of view of computational efficiency (in time and space) and from the point of view of plan quality relative to its feasibility. We discuss advantages and disadvantages of each strategy in the light of experimental results.

A Discrete Differential Evolution Algorithm for the Total Flowtime Flowshop Scheduling Problem
SPEAKER: unknown

ABSTRACT. In this paper a new discrete Differential Evolution algorithm for the Permutation Flowshop Scheduling Problem with the total flowtime criterion is proposed. The core of the algorithm is the distance-based differential mutation operator defined by means of a new randomized bubble sort algorithm. This mutation scheme allows the Differential Evolution to directly navigate the permutations search space. Experiments were held on a well known benchmark suite and the results show that our proposal outperforms state-of-the-art algorithms in the majority of the problems.

16:00-16:30Coffee Break
16:30-19:00 Session 79A: VSL Joint Award Ceremony 1
Location: MB, Kuppelsaal
Foundations and Technology Competitions Award Ceremony

ABSTRACT. The third round of the Kurt Gödel Research Prize Fellowships Program, under the title: Connecting Foundations and Technology, aims at supporting young scholars in early stages of their academic careers by offering highest fellowships in history of logic, kindly supported by the John Templeton Foundation. Young scholars being less or exactly 40 years old at the time of the commencement of the Vienna Summer of Logic (July 9, 2014) will be awarded one fellowship award in the amount of EUR 100,000, in each of the following categories:

  • Logical Foundations of Mathematics,
  • Logical Foundations of Computer Science, and
  • Logical Foundations of Artificial Intelligence

The following three Boards of Jurors were in charge of choosing the winners:

  • Logical Foundations of Mathematics: Jan Krajíček, Angus Macintyre, and Dana Scott (Chair).
  • Logical Foundations of Computer Science: Franz Baader, Johann Makowsky, and Wolfgang Thomas (Chair).
  • Logical Foundations of Artificial Intelligence: Luigia Carlucci Aiello, Georg Gottlob (Chair), and Bernhard Nebel.


FLoC Olympic Games Award Ceremony 1

ABSTRACT. The aim of the FLoC Olympic Games is to start a tradition in the spirit of the ancient Olympic Games, a Panhellenic sport festival held every four years in the sanctuary of Olympia in Greece, this time in the scientific community of computational logic. Every four years, as part of the Federated Logic Conference, the Games will gather together all the challenging disciplines from a variety of computational logic in the form of the solver competitions.

At the Award Ceremonies, the competition organizers will have the opportunity to present their competitions to the public and give away special prizes, the prestigious Kurt Gödel medals, to their successful competitors. This reinforces the main goal of the FLoC Olympic Games, that is, to facilitate the visibility of the competitions associated with the conferences and workshops of the Federated Logic Conference during the Vienna Summer of Logic.

This award ceremony will host the

  • 3rd Confluence Competition (CoCo 2014);
  • Configurable SAT Solver Challenge (CSSC 2014);
  • Ninth Max-SAT Evaluation (Max-SAT 2014);
  • QBF Gallery 2014; and
  • SAT Competition 2014 (SAT-COMP 2014).
FLoC Closing Week 1
SPEAKER: Helmut Veith