Maurice Bruynooghe's research while affiliated with KU Leuven and other places

Publications (320)

Article
Aggregates provide a concise way to express complex knowledge. The problem of selecting an appropriate formalization of aggregates for answer set programming (ASP) remains unsettled. This paper revisits it from the viewpoint of Approximation Fixpoint Theory (AFT). We introduce an AFT formalization equivalent with the Gelfond–Lifschitz reduct for ba...
Preprint
Aggregates provide a concise way to express complex knowledge. While they are easily understood by humans, formalizing aggregates for answer set programming (ASP) has proven to be challenging . The literature offers many approaches that are not always compatible. One of these approaches, based on Approximation Fixpoint Theory (AFT), has been develo...
Preprint
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Parity games are infinite two-player games played on directed graphs. Parity game solvers are used in the domain of formal verification. This paper defines parametrized parity games and introduces an operation, Justify, that determines a winning strategy for a single node. By carefully ordering Justify steps, we reconstruct three algorithms well kn...
Chapter
Parity games are infinite two-player games played on node-weighted directed graphs. Formal verification problems such as verifying and synthesizing automata, bounded model checking of LTL, CTL*, propositional -calculus, ... reduce to problems over parity games. The core problem of parity game solving is deciding the winner of some (or all) nodes in...
Conference Paper
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The presence of symmetry in Boolean satisfiability (SAT) problem instances often poses challenges to solvers. Currently, the most effective approach to handle symmetry is by static symmetry breaking, which generates asymmetric constraints to add to the instance. An alternative way is to handle symmetry dynamically during solving. As modern SAT solv...
Article
In answer set programming (ASP), programs can be viewed as specifications of finite Herbrand structures. Other logics can be (and, in fact, were) used toward the same end and can be taken as the basis of declarative programming systems of similar functionality as ASP. We discuss here one such logic, the logic FO(ID), and its implementation IDP3. Th...
Article
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Symmetry in combinatorial problems is an extensively studied topic. We continue this research in the context of model expansion problems, with the aim of automating the workflow of detecting and breaking symmetry. We focus on local domain symmetry, which is induced by permutations of domain elements, and which can be detected on a first-order level...
Article
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The IDP knowledge base system currently uses MiniSAT(ID) as its backend Constraint Programming (CP) solver. A few similar systems have used a Mixed Integer Programming (MIP) solver as backend. However, so far little is known about when the MIP solver is preferable. This paper explores this question. It describes the use of CPLEX as a backend for ID...
Article
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Mining frequent tree patterns has many practical applications in different areas such as XML data, bioinformatics and World Wide Web. The crucial step in frequent pattern mining is frequency counting which involves performing a matching operator to find occurrences (instances) of a pattern tree in database trees. A widely used matching operator for...
Conference Paper
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An effective SAT preprocessing technique is the construction of symmetry breaking formulas: auxiliary clauses that guide a SAT solver away from needless exploration of symmetric subproblems. However, during the past decade, state-of-the-art SAT solvers rarely incorporated symmetry breaking. This suggests that the reduction of the search space does...
Article
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Declarative systems aim at solving tasks by running inference engines on a specification, to free their users from having to specify how a task should be tackled. In order to provide such functionality, declarative systems themselves apply complex reasoning techniques, and, as a consequence, the development of such systems can be laborious work. In...
Article
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To appear in Theory and Practice of Logic Programming (TPLP). Dynamic systems play a central role in fields such as planning, verification, and databases. Fragmented throughout these fields, we find a multitude of languages to formally specify dynamic systems and a multitude of systems to reason on such specifications. Often, such systems are bound...
Article
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Finding satisfying assignments for the variables involved in a set of constraints can be cast as a (bounded) model generation problem: search for (bounded) models of a theory in some logic. The state-of-the-art approach for bounded model generation for rich knowledge representation languages, like ASP, FO(.) and Zinc, is ground-and-solve: reduce th...
Article
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With the technology of the time, Kowalski's seminal 1974 paper Predicate Logic as a Programming Language was a breakthrough for the use of logic in computer science. The more recent tremendous progress in automated reasoning technologies, particularly in SAT solving and Constraint Programming, has paved the way for the use of logic as a modelling l...
Article
Metrics for structured data have received an increasing interest in the machine learning community. Graphs provide a natural representation for structured data, but a lot of operations on graphs are computationally intractable. In this article, we present a polynomial-time algorithm that computes a maximum common subgraph of two outerplanar graphs....
Article
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This paper explores the use of predicate logic as a modeling language. Using IDP3, a finite model generator that supports first order logic enriched with types, inductive definitions, aggregates and partial functions, search problems stated in a variant of predicate logic are solved. This variant is introduced and applied on a range of problems ste...
Article
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Recent work in Answer Set Programming has integrated ideas from Constraint Programming. This has led to a new field called ASP Modulo CSP (CASP), in which the ASP language is enriched with constraint atoms representing constraint satisfaction problems. These constraints have a more compact grounding and are handled by a new generation of search alg...
Article
Monte Carlo tree search (MCTS) is a sampling and simulation based technique for searching in large search spaces containing both decision nodes and probabilistic events. This technique has recently become popular due to its successful application to games, e.g. Poker Van den Broeck et al. (2009) and Go Coulom (2006); Chaslot et al. (2006); Gelly an...
Article
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Designers often apply manual or semi-automatic loop and data transformations on array and loop intensive programs to improve performance. It is crucial that such transformations preserve the functionality of the program. This paper presents an automatic method for constructing equivalence proofs for the class of static affine programs. The equivale...
Article
This paper considers the fragment ∃∀SO of second-order logic. Many interesting problems, such as conformant planning, can be naturally expressed as finite domain satisfiability problems of this logic. Such satisfiability problems are computationally hard (ΣP2) and many of these problems are often solved approximately. In this paper, we develop a ge...
Conference Paper
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This paper reports on the use of the FO(·) language and the IDP framework for modeling and solving some machine learning and data mining tasks. The core component of a model in the IDP framework is an FO(·) theory consisting of formulas in first order logic and definitions; the latter are basically logic programs where clause bodies can have arbitr...
Article
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Development of acute kidney injury (AKI) during the postoperative period is associated with increases in both morbidity and mortality. The aim of this study is to develop a statistical model capable of predicting the occurrence of AKI in patients after elective cardiac surgery.
Article
Many examples of epistemic reasoning in the literature exhibit a stratified structure: defaults are formulated on top of an incomplete knowledge base. These defaults derive extra information in case information is missing in the knowledge base. In autoepistemic logic, default logic and ASP this inherent stratification is not preserved as they may r...
Conference Paper
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Approximation Fixpoint Theory was developed as a fixpoint theory of lattice operators that provides a uniform formalization of four main semantics of three major nonmonotonic reasoning formalisms. This paper clarifies how this fixpoint theory can define the stable and well-founded semantics of logic programs. It investigates the notion of strong eq...
Article
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The intensive care unit (ICU) length of stay (LOS) of patients undergoing cardiac surgery may vary considerably, and is often difficult to predict within the first hours after admission. The early clinical evolution of a cardiac surgery patient might be predictive for his LOS. The purpose of the present study was to develop a predictive model for I...
Article
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Today, many different probabilistic programming languages exist and even more inference mechanisms for these languages. Still, most logic programming based languages use backward reasoning based on SLD resolution for inference. While these methods are typically computationally efficient, they often can neither handle infinite and/or continuous dist...
Article
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We introduce an abductive method for a coherent integration of independent data-sources. The idea is to compute a list of data-facts that should be inserted to the amalgamated database or retracted from it in order to restore its consistency. This method is implemented by an abductive solver, called Asystem, that applies SLDNFA-resolution on a meta...
Conference Paper
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Much research in logic programming and non-monotonic reasoning originates from dissatisfaction with classical logic as a knowledge representation language, and with classical deduction as a mode for automated reasoning. Discarding these classical roots has generated many interesting and fruitful ideas. However, to ensure the lasting impact of the r...
Conference Paper
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This paper integrates Pearl's seminal work on probability and causality with that of Shafer. Using the language of CP-logic, it transposes Pearl's analysis of interventions and counterfactuals to the se- mantic context of Shafer's probability trees. This gives us definitions that work not on the level of random variables, but on the level of Humean...
Article
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Constraint propagation is one of the basic forms of inference in many logic-based reasoning systems. In this paper, we investigate constraint propagation for first-order logic (FO), a suitable language to express a wide variety of constraints. We present an algorithm with polynomial-time data complexity for constraint propagation in the context of...
Article
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This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes according to the time they need to reach a stable state after coronary bypass surgery: less or more than 9 h. On the basis of five physiological variables (heart rate, sy...
Article
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Probability trees are decision trees that predict class probabilities rather than the most likely class. The pruning criterion used to learn a probability tree strongly influences the size of the tree and thereby also the quality of its probability estimates. While the effect of pruning criteria on classification accuracy is well-studied, only rece...
Article
Full-text available
Constraint propagation is one of the basic forms of inference in many logic-based reasoning systems. In this paper, we investigate constraint propagation for first-order logic (FO), a suitable language to express a wide variety of constraints. We present an algorithm with polynomial time data-complexity for constraint propagation in the context of...
Conference Paper
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We introduce First Order ProbLog, an extension of first order logic with soft constraints where formulas are guarded by probabilistic facts. The paper defines a semantics for FOProbLog, develops a translation into ProbLog, a system that allows a user to compute the probability of a query in a similar setting restricted to Horn clauses, and reports...
Conference Paper
This paper considers the fragment there exists for all SO of second-order logic. Many interesting problems, such as conformant planning, can be naturally expressed as finite domain satisfiability problems of this logic. Such satisfiability problems are computationally hard (Sigma(P)(2)) and many of these problems are often solved approximately. In...
Article
Full-text available
The application of loop and data transformations to array and loop intensive programs is crucial to obtain a good performance. Designers often apply these transformations manually or semi-automatically. For the class of static affine programs, automatic methods exist for proving the correctness of these transformations. Realistic multimedia systems...
Conference Paper
Proving termination of, or generating efficient control for Constraint Handling Rules (CHR) programs requires information about the kinds of constraints that can show up in the CHR constraint store. In contrast to Logic Programming (LP), there are not many tools available for deriving such information for CHR. Hence, instead of building analyses fo...
Conference Paper
Full-text available
Designers often apply manual or semi-automatic loop and data transformations on array and loop intensive programs to improve performance. The transformations should preserve the functionality, however, and this paper presents an automatic method for constructing equivalence proofs for the class of static affine programs. The equivalence checking is...
Article
Full-text available
There are many interesting Knowledge Representation questions surrounding rule languages for the Semantic Web. The most basic one is of course: which kind of rules should be used and how do they integrate with existing Description Logics? Similar questions have already been addressed in the field of Logic Programming, where one particular answer ha...
Article
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This papers develops a logical language for representing probabilistic causal laws. Our interest in such a language is twofold. First, it can be motivated as a fundamental study of the representation of causal knowledge. Causality has an inherent dynamic aspect, which has been studied at the semantical level by Shafer in his framework of probabilit...
Article
Computerization in healthcare in general, and in the operating room (OR) and intensive care unit (ICU) in particular, is on the rise. This leads to large patient databases, with specific properties. Machine learning techniques are able to examine and to extract knowledge from large databases in an automatic way. Although the number of potential app...
Article
Full-text available
This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes according to the time they need to reach a stable state after coronary bypass surgery: less or more than nine hours. On the basis of five physiological variables differen...
Conference Paper
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We report on two exercises in modeling, in- ference and learning with seven statistical re- lational learning systems and use this as a ba- sis for a simple and preliminary comparison between these systems.
Conference Paper
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In machine learning, there has been an increased interest in metrics on structured data. The application we focus on is drug discovery. Although graphs have become very popular for the representation of molecules, a lot of operations on graphs are NP-complete. Representing the molecules as outerplanar graphs, a subclass within general graphs, and u...
Conference Paper
Type information has many applications, it can be used for optimized compilation, termination analysis, error detection, . . . . How- ever logic programs are typically untyped. A well-typed program has the property that it behaves identically with or without type checking. Hence the automatic inference of a well-typing is worthwhile. Existing infer...
Article
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This paper introduces a novel method for learning a wrapper for extraction of information from web pages, based upon (k,l)-contextual tree languages. It also introduces a method to learn good values of k and l based on a few positive and negative examples. Finally, it describes how the algorithm can be integrated in a tool for information extractio...
Conference Paper
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We investigate the satisfiability problem, SAT(ID), of an extension of propositional logic with inductive definitions. We demonstrate how to extend existing SAT solvers to become SAT(ID) solvers, and provide an implementation on top of MiniSat. We also report on a performance study, in which our implementation exhibits the expected benefits: full u...
Conference Paper
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In reinforcement learning problems, an agent has the task of learning a good or optimal strategy from interaction with his environment. At the start of the learning task, the agent usually has very little information. Therefore, when faced with complex problems that have a large state space, learning a good strategy might be infeasible or too slow...
Article
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Recently, there has been an increasing interest in directed probabilistic logical models and a variety of formalisms for describing such models has been proposed. Although many authors provide high-level arguments to show that in principle models in their formalism can be learned from data, most of the proposed learning algorithms have not yet been...
Article
Full-text available
In this study we present a combination of time-series anal-ysis tools and a machine learning algorithm (Gaussian Pro-cess classifier) for the task of predicting the time frame in which the minimal clinical conditions of stability to start weaning of mechanical ventilation are reached. We per-form a retrospective analysis of clinical data obtained f...
Article
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Standard databases convey Reiter's closed-world assumption that an atom not in the database is false. This assumption is relaxed in locally complete databases that are sound but only partially complete about their domain. One of the consequences of the weakening of the closed-world assumption is that query answering in locally closed databases is n...
Article
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The goal of transfer learning algorithms is to utilize knowledge gained in a source task to speed up learning in a different but related target task. Recently, several transfer methods for reinforcement learning have been proposed. A lot of them require a mapping that relates features from the source task to those of the target task, and most of th...
Conference Paper
Full-text available
Standard databases convey Reiter's closed-world as- sumption that an atom not in the database is false. This assumption is relaxed in locally closed databases that are sound but only partially complete about their do- main. One of the consequences of the weakening of the closed-world assumption is that query answering in locally closed databases is...
Article
Type information has many applications, it can be used for opti- mized compilation, termination analysis, error detection, . . . . How- ever logic programs are typically untyped. A well-typed program has the property that it behaves identically with or without type checking. Hence the automatic inference of a well-typing is worth- while. Existing i...
Conference Paper
String based as well as tree based methods have been used to learn wrappers for extraction from semi-structured docu- ments (e.g., HTML documents). Previous work has shown that tree based approaches perform better while needing less examples than string based approaches. A disadvantage is that they can only extract complete text nodes, whereas stri...
Conference Paper
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The polytope model is widely used in compiler analysis for representing a certain class of programs. Many counting problems that occur in the analysis of such pro- grams can be solved by counting the number of integer points in a parametric polytope. In other counting problems, poly- nomial weights are assigned to the integer points of a para- metr...
Article
Development of energy and performance-efficient embedded software is increasingly relying on application of complex transformations on the critical parts of the source code. Designers applying such nontrivial source code transformations are often faced with the problem of ensuring functional equivalence of the original and transformed programs. Cur...
Conference Paper
Full-text available
Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although many authors provide high-level arguments to show that in principle models in their language can be learned from data, most of the proposed learning algorithms have not yet been s...
Article
Full-text available
This paper presents a novel method to construct a dynamic single assignment (DSA) form of array intensive, pointer free C programs. A program in DSA form does not perform any destructive update of scalars and array elements; that is, each element is written at most once. As DSA makes the dependencies between variable references explicit, it facilit...
Article
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In many scenarios, a database instance violates a given set of integrity constraints. In such cases, it is often required to repair the database, that is, to re- store its consistency. A primary motif behind the repairing approaches is the principle of minimal change, which is the aspiration to keep the recovered data as faithful as possible to the...
Conference Paper
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We discuss how to learn non-recursive directed probabilistic logical models from relational data. This problem has been tackled before by upgrading the structure-search algorithm initially proposed for Bayesian networks. In this paper we propose to upgrade another algorithm, namely ordering-search, since for Bayesian networks this was found to work...
Article
In this paper we describe the application of data mining methods for predicting the evolution of patients in an intensive care unit. We discuss the importance of such methods for health care and other application domains of engineering. We argue that this problem is an important but challenging one for the current state of the art data mining metho...
Conference Paper
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There is an increasing interest in upgrading Bayesian networks to the relational case, resulting in directed probabilistic logical models. Many formalisms to describe such models have been introduced and learning algorithms have been developed for several such formalisms. Most of these algorithms are upgrades of the traditional structure search alg...
Article
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Many compiler optimization techniques depend on the ability to calculate the number of elements that satisfy certain conditions. If these conditions can be represented by linear constraints, then such problems are equivalent to counting the number of integer points in (possibly) parametric polytopes. It is well known that the enumerator of such a s...
Article
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Abstract In this paper, we present a framework for the semantics and the computation of aggregates in the context of logic programming. In our study, an aggregate can be an arbitrary interpreted second order predicate or function. We define extensions of the Kripke-Kleene, the well-founded and the stable semantics for aggregate programs. The semant...
Article
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This article makes two contributions to the work on semantics-based termination analysis for logic programs. The first involves a novel notion of type-based norm where for a given type, a corresponding norm is defined to count in a term the number of subterms of that type. This provides a collection of candidate norms, one for each type defined in...