Ulrich Junker

A technique for detecting missing rules (mr) with most general conditions in a rule project (1) having a given scope with a fixed number of objects of a given type, wherein each rule (r) is defined by at least one test (t) in respect to at least one condition of at least one attribute (age, value) of the object, the method comprising the steps of f...

A method, system and computer program product for minimizing a rule set. A rule set application graph that describes a set of rules including actions and cases is built, whereby each rule defines an action for one or more cases. A rule violation graph for each rule describing the actions and cases not defined for that rule is built. A subset of rul...

A missing case of a fixed scope can be detected among a plurality of business rules of unrestricted forms. According to one or more embodiments, the described detecting includes building a rules inhibition graph for the plurality of business rules representing a constraint model comprising a plurality of nodes and describing a plurality of cases wh...

A method (1500) for generating a Generalized Missing Rule (GMR). The method involves receiving descriptions of First Scopes (FSs) that are admissible for a First Rule Project (FRP). FRP comprises first rules. Each FS is defined by at least one object characterizing a case. An Expanded Set of Scope Descriptions (ESSD) is generated by adding descript...

The European air traffic flow management problem poses particular challenges on optimization technology as it requires detailed modelling and rapid online optimization capabilities. Constraint programming proved successful in addressing these challenges for departure time slot allocation by offering fine-grained modelling of resource constraints an...

We consider constructive approaches to decision making which allow incomplete preference orders over multiple criteria. Whereas additional preferences may be acquired during the decision making process, the set of criteria is usually kept fixed. In this paper, we study the addition of new criteria and examine how this may refine or even reverse the...

Partial orders provide a convenient way to express preferences on multiple criteria. Prominent examples are Pareto-dominance and the preference relations of (T)CP-nets. In advanced personalized recommender systems, the user may also specify a partial order over the possible values of a single criterion. We introduce a technique called outer branchi...

This editorial explains the benefits of preferences for Al systems and draws a picture of cur rent Al research on preference handling It thus provides an Introduction to the topics covered by this special issue on preference handling.

A decision policy chooses an outcome dependent on given input parameters. Policies can adequately be represented by production rules, which are at the heart of modern business rule management systems. Classic ways of policy design are rule authoring by experts or learning from data. In this paper, we show that policies can also be derived from a mo...

The article presents essays from the configuration workshop held in August 2006 as part of ECAI in Riva del Garda, Italy. The essays address reasoning techniques, user interaction, business integration, and finally presents a practical case study. These essays aim to give the readers insight into current trends and challenges in configuration. If y...

Specific preference statements may reverse general prefer- ence statements, thus constituting a change of attitude in par- ticular situations. We define a semantics of preference rever- sal by relaxing the popular ceteris-paribus principle. We char- acterize preference reversal as default reasoning and we link it to prioritized Pareto-optimization,...

Constraint Programming (CP) and Satisability Modulo Theories (SMT) both generalize SAT w.r.t. expressiveness and propagation power. CP uses domain propagators based on mathematical structures, whereas SMT uses constraint propagators based on logical theories. In this paper, we incorporate SMT reasoning into CP and illustrate the benefits of the res...

This chapter explains that configuration is the task of composing a customized system out of generic components. This task is of universal concern as component-based systems are omnipresent in modern industry. Components are generic in nature and can be produced in mass, however are destined to support customized solutions. The available components...

We review the backtracking technique of Doyle's Truth Maintenance System (TMS). Backtracking in principle is to recover from a failure state by retracting some assumptions. We discuss three possible applications for the TMS: (1) Transforming a contradiction proof into a direct proof if a false-node is labelled with In. (2) Selecting another extensi...

We use a lexicographical preference order on the problem space to combine solution synthesis with conict learning. Given two preferred solutions of two subproblems, we can either combine them to a solution of the whole problem or learn a 'fat' conict which cuts off a whole subtree. The approach makes conict learning more per- vasive for Constraint...

Inconsistency proving of CSPs is typically achieved by a combination of systematic search and arc consistency, which can both be characterized as resolution. However, it is well-known that there are cases where resolution produces exponential contradiction proofs, although proofs of polynomial size exist. For this reason, we will use optimization m...

Many real-world AI problems (e.g., in configuration) are weakly constrained, thus requiring a mechanism for characterizing and finding the preferred solutions. Preference-based search (PBS) exploits preferences between decisions to focus search to preferred solutions, but does not efficiently treat preferences on global criteria such as the total p...

Preference programming provides a new paradigm for expressing (default) decisions, preferences between decisions, and search strategies in a declarative and unified way and for embedding them in a constraint and rule language. Business experts can thus directly specify preferences and search directives in form of rules without needing to program se...

This paper describes the logic of ILOG (J)Configurator, a powerful configuration sys- tem combining constraint programming with a description logic. This combination is based on two key ideas: 1. Constraints are embedded into a logical language and can thus be applied to logical terms formed with the vocabulary of the description logic. 2. When sol...

Over-constrained problems can have an exponential number of conflicts, which explain the failure, and an exponential number of relaxations, which restore the consistency. A user of an interactive application, however, desires explanations and relaxations containing the most important constraints. To address this need, we define preferred explanatio...

ii PREFACE Constraint satisfaction is a successful paradigm developed by the AI community that found acceptance in many fields of computer science. While specific techniques (e.g. operations research ones) exist for most of the problems that can be represented as Constraint Satisfaction Problems (CSPs), constraint satisfaction owes its success to t...

Combinatorial problems such as scheduling, resource allocation, and configuration have many attributes that can be subject of user preferences. Traditional optimization approaches compile those preferences into a single utility function and use it as the optimization objective when solving the problem, but neither explain why the resulting solution...

Configuration problems often involve large product catalogs, and the given user requests can be met by many different kinds of parts from this catalog. Hence, configuration problems are often weakly constrained and have many solutions. However, many of those solutions may be discarded by the user as long as more interesting solutions are possible....

We present an algorithm Pref-AC that limits arc consistency (AC) to the preferred choices of a tree search procedure and that makes constraint solv­ ing more efficient without changing the pruning and shape of the search tree. Arc consistency thus becomes more scalable and usable for many real- world constraint satisfaction problems such as con­ fi...

Airline crew assignment problems are large-scale optimization problems which can be adequately solved by column generation. The subproblem is typically a so-called constrained shortest path problem and solved by dynamic programming. However, complex airline regulations arising frequently in European airlines cannot be expressed entirely in this fra...

Existing conflict detection methods for CSP's such as [de Kleer, 1989; Ginsberg, 1993] cannot make use of powerful propagation which makes them unusable for complex real-world problems. On the other hand, powerful constraint propagation methods lack the ability to extract dependencies or conflicts, which makes them unusable for many advanced AI rea...

. Column generation is a state-of-the-art method for optimally solving difficult large-scale optimization problems such as airline crew assignment. We show how to apply column generation even if those problems have complex constraints that are beyond the scope of pure OR methods. We achieve this by formulating the subproblem as a constraint satisfa...

Preference-based search (PBS) is a new search procedure for solving combinatorial optimization problems. Given a set of preferences between search decisions, PBS searches through a space of preferred solutions, which is tighter than the space of all solutions. The definition of preferred solutions is based on work in non-monotonic reasoning (Brewka...

Column generation is a state-of-the-art method for optimally solving difficult large-scale optimization problems such as airline crew assignment. We show how to apply column generation even if those problems have complex constraints that are beyond the scope of pure OR methods. We achieve this by formulating the subproblem as a constraint satisfact...

Introduction Crew scheduling at airlines is usually divided into a crew pairing and a crew assignment (or rostering) phase. Firstly, anonymous pairings (or crew rotations) are formed out of the flight legs (flights without stopover) such that the crew needs on each flight are covered. Then in crew assignment, the pairings together with other activi...

Finding good problem decompositions is crucial for solving large-scale key/lock configuration problems. We present a novel approach to problem decomposition where the detection of a subproblem hierarchy is formulated as a constraint satisfaction problem (CSP) on set variables. Primitive constraints on set variables such as an inverse and a union-ov...

Explicit preferences on assumptions as used in prioritized circumscription (McCarthy, 1986; Lifschitz, 1985; Grosof, 1991) and preferred subtheories (Brewka, 1989) provide a clear and declarative method for defining preferred mod­ els. In this paper, we show how to embed preferences in the logical theory itself. This gives a high freedom for expres...

Nous développons un système, dénommé SISMONAUTE, d'aide aux géophysiciens pour l'étude de la propagation des ondes dans un modèle postulé de sous-sol. Le système suit les fronts d'onde dans une série d'instantanés 2D produits par un simulateur numérique. De plus, il rétablit l'historique de l'onde, c'est-à-dire la séquence des réflexions, transmiss...

Dynamic objects such as liquids, waves, and flames can easily change their position, shape, and number. Snapshot images produced by finite element simulators show these changes, hut lack an explicit representation of the objects and their causes. For the example of seismic waves, we develop a method for interpreting snapshots which is based on Haye...

Preferences between diagnostic assumptions are needed to handle interactions between different kinds of assumptions and to focus the diagnostic process to components that are more likely to fail. We investigate different preference criteria and relate them to search strategies in Reiter's hitting trees. In particular, we consider a partial order on...

this report contains a user manual, as well as examples that demonstrate how default reasoning is applied practically. Additionally, this report provides some technical information about Except II. Thus, people interested in non-monotonic reasoning or automated deduction may gain some insights how to implement a default prover. Last, but not least,...

Without Abstract

We demonstrate the technological value of non- monotonic logics by an example: We use prior- itized defaults for candidate generation in diag- nosis from first principles. We implement this non-monotonic logic by TMS similar to default logic. Prioritized defaults allow an easy formu­ lation of a diagnosis problem including state­ ments such as 'ele...

In this paper we develop a proof procedure for autoepistemic (AEL) and default logics (DL), based on translating them into a Truth Maintenance System (TMS). The translation is decidable if the theory consists of a finite number of defaults and premises and classical derivability for the base language is decidable. To determine all extensions of a n...

In this paper, we investigate technical methods to deal with exceptions, inconsistencies, and ambiguity. Existing reason maintenance systems are only suitable for some of these problems. Doyle's TMS handles exceptions properly, but gets in trouble with non-monotonic odd or even loops. On the other hand, de Kleer's ATMS produces too many contexts if...

Wir entwickeln in diesem Papier Beweiser für Moore’s autoepistemische Logik (AEL) und Reiter’s Defaultlogik (DL), die alle Extensionen bestimmen und auch inkohärente Theorien (d.h. solche ohne Extension) bearbeiten können. Allerdings betrachten wir nur endliche Theorien und fordern, daß die klassische Ableitbarkeit für die zugrundeliegende Sprache...

In our research group, the hybrid knowledge representation system Babylon has been developed providing formalisms for rules, prolog and frames. Beyond it, we implemented Consat, a system for con­ straint satisfaction. Since applications of Babylon for process diagnosis, planning etc. required constraints. we integrated Consat into the Babylon envir...

Dynamic objects such as liquids, waves, and flames can easily change their position, shape, and number. Snapshot images produced by fi-nite element simulators show these changes, hut lack an explicit representation of the objects and their causes. For the example of seismic waves, we develop a method for interpreting snapshots which is based on Hay...

Kaiserslautern, Univ., Diss., 1992.