Preference Handling

Logic programs with ordered disjunction have shown to be a flexible specification language able to model common user preferences in a natural way. However, in some realistic scenarios the preferences should be linked to the evidence of the information when trying to reach a single preferred solution. In this paper, we extend the syntax and the semantics of logic programs with ordered disjunction in order to cope with uncertain information. In particular, we define a possibilistic semantics for capturing possibilistic ordered disjunction programs. We use a simple example to explain the approach and outline an application scenario showing the benefits of possibilistic ordered disjunction.

Numerous studies show that there is relationship between skilled performance and body organs dominants, such as hands, feet and eyes. In order to compare the performance of left and right basketball lay-up in ipsilateral and contralateral conditions of hands and feet in male students of Tabriz Islamic Azad University, 100 male student were selected by a described questionnaires, Chapman-Chapman hand superiority and Wai-Hong Jackie Lam foot superiority and were randomly divided into four groups: 1) 30 right ipsilateral, 2) 30 left ipsilateral, 3) 20 right contralateral and 4) 20 left contralateral. Participants tried left and right lay-up in 150 trials for 5 days and finally 10 efforts for an optimal test were conducted. Data was analyzed by variance of 2 × 4 combined design within and between groups, and Bonferroni test. By analyzing the proposed hypotheses at the P≤ 0.01 demonstrated significant differences among groups in performance. In general, contralateral students, especially right contralaterals had better performance compared with other groups.

Background and Objectives: This study aims to determine the relationship between hand dominance and ocular dominance (OD) using different test formats of handedness and ocular dominance. Methods: Three OD test formats were administered to 74 healthy young adult subjects, hole-incard test for sighting dominance, near-point-of-convergence (NPC) test for motor dominance, and +1.50 to blur test for sensory dominance. All of these tests were performed while the best correction was in front of the subject's eyes. An interview for preferred dominance and a finger-tapping test for performance dominance were administered to determine the dominant hand. Results: Right eye dominance was indicated in 66.2% with the hole-in-card test, 56.8% with the NPC test, and 51.4% of cases with the +1.50-to-blur test. Statistically, a significant nonrandom relationship was observed between the results of hole-in-card and NPC tests (P=0.000), hole-incard and +1.50-to-blur tests (P=0.003), and also between the results of NPC and +1.50-to-blur tests (P=0.003). In addition, it was found that in 52.7% of the cases, all three dimensions of eye dominance (sighting, sensory, and motor) are not in the same eye and do not have pure eye dominance. In examining the dominant hand, the majority of subjects were right-handed both in the preference (62 of 74 [83.8%]) and in the performance dimension (63 of 74 [85.1%]). Statistical analysis shows a significant nonrandom relationship between the pure dominant hand and the pure dominant eye (P=0.000). In addition, the pure dominant hand (0.813) and pure dominant eye (P=0.126) are independent of gender. Conclusion: Determining the OD, similar to determining the hand dominance based on their different dimensions, can have different results. According to the results, in all dimensions of ocular and hand dominance, both the dominant eye and the dominant hand are more on the right side of people. Furthermore, the pure dominant eye and pure dominant hand are not independent of each other.

The purpose of this research was to compare the performance of right basketball lay-up in hands and feet ipsilateral and contralateral conditions in university students, 100 male students were selected by a described questionnaires, Chapman-...

We address the problem of reasoning about preferences among properties (outcomes, desiderata, etc.) in Reiter's default logic. Preferences are expressed using an ordered default theory, consisting of default rules, world knowledge, and an ordering, reflecting preference, on the default rules. In contrast with previous work in the area, we do not rely on prioritised versions of default logic, but rather we transform an ordered default theory into a second, standard default theory wherein the preferences are respected, in that defaults are applied in the prescribed order. This translation is accomplished via the naming of defaults, so that reference may be made to a default rule from within a theory. In an elaboration of the approach, we allow an ordered default theory where preference information is specified within a default theory. Here one may specify preferences that hold by default, in a particular context, or give preferences among preferences. In the approach, one essentially axiomatises how different orderings interact within a theory and need not rely on metatheoretic characterisations. As well, we can immediately use existing default logic theorem provers for an implementation. From a theoretical point of view, this shows that the explicit representation of priorities among defaults adds nothing to the overall expressibility of default logic.

The purpose of this research was to compare the performance of right basketball lay-up in hands and feet ipsilateral and contralateral conditions in university students, 100 male students were selected by a described questionnaires, Chapman - Chapman hand superiority and Wai - Hong Jackie Lam foot superiority and were randomly divided into four groups: 1) 30 right ipsilateral, 2) 30 left ipsilateral, 3) 20 right contralateral and 4) 20 left contralateral. Participants tried right basketball lay-up in 75 trials for 5 days, and finally 5 efforts for an optimal test were conducted. Data were analyzed by analysis variance to compare the mean scores of groups, and LSD pursuit test was used in case of significant effect of different ipsilateral and contralateral conditions. By analyzing the proposed hypotheses at the P≤ 0.01 demonstrated significant differences among groups in performance. In general, contralateral students, especially right contralaterals had better performance compared ...

Various researches know lateral preference of eye and hand pattern as one of the important factors of performing sports skills. This study aimed at investigating the effect of lateral preference of eye and hand pattern on learning basketball free throw skill. From 3000 female students of Shahid Chamran University of Ahvaz, 60 subjects (age range 19-22 yr) were selected purposively as the sample using a researcher-made questionnaire of individual information and sporting background, Edinburgh Handedness Inventory (Oldfield, 1971) and hole card (Durand and Gold, 1910) and were assigned to two control and experimental groups (each group: 15 unilateral subjects and 15 crossed-lateral subjects). Firstly, pretest of basketball free throw was conducted. Then, practice protocol was performed for 8 weeks (24 sessions, 3 sessions a week). During this period, 6 posttests were administered to determine learning stages and one week after the last posttest, the retention test was conducted. The results showed a significant difference between unilateral and crossed-lateral (experimental group) subjects in the cognitive (sig=0.000) and associative (sig=0.000) stages of the acquisition of basketball free throw and the unilateral subjects had a better performance. Whereas there was no significant difference between unilateral and crossed-lateral subjects in the autonomous (sig=0.105) and retention (sig=0.086) stages. Finally, the results showed a difference in performance between experimental and control groups in favor of experimental group. According to these results, it seems that long practice and autonomous skill in unilateral and crossed-lateral subjects matched their performance and eliminated their differences. Therefore, coaches are recommended to identify talented subjects after a lot of practice in order to not generalize the result of performance to learning.

Reasoning about preferences is a major issue in many decision making problems. Recently, a new logic for handling preferences, called Qualitative Choice Logic (QCL), was presented. This logic adds to classical propositional logic a new connective, called ordered disjunction symbolized by ×. That new connective is used to express preferences between alternatives. QCL was not designed to handle conditional preferences, even if it is possible to express an implication with a preference on the left hand side, for instance "(Air France × Virgin) ⇒ Hotel Package". However, using QCL semantics, there is no difference between such material implication "(Virgin × Air France) ⇒ Hotel Package" and the purely propositional formula "(Air France ∨ Virgin) ⇒ Hotel Package ". Indeed, the negation in QCL gets rid of nested ordered disjunctions. Furthermore, the negation in QCL misses some desirable properties from propositional calculus. In this paper, we present a new semantics for the QCL language that addresses those problems. We describe a general framework for handling qualitative preferences. That framework is based on normal form functions that transform general QCL formulas into basic choice formulas, which are simple formulas (ordered disjunction of propositional formulas). We formulate the properties of our normal form function that overcome current QCL limitations.

Internet and mobile applications are becoming more and more helpful and widespread, while our daily lives are becoming increasingly busy and complicated. Preferences affect our actions, as well as those of intelligent agents. Answer Set Programming is a suitable framework for a decision making process which aims at supporting users by suitably planning their activities. Resourced Answer Set Programming (RASP) provides mechanisms for the optimization of answer sets according to preferences and resources. In this paper, an ASP-based system integrated with a mobile application able to plan the activities of a user is proposed, taking into account the context in which the user is located, the available resources, the geographical position and user's preferences.

We address the problem of reasoning about preferences among properties (outcomes, desiderata, etc.) in Reiter's default logic. Preferences are expressed using an ordered default theory, consisting of default rules, world knowledge, and an ordering, reflecting preference, on the default rules. In contrast with previous work in the area, we do not rely on prioritised versions of default logic, but rather we transform an ordered default theory into a second, standard default theory wherein the preferences are respected, in that defaults are applied in the prescribed order. This translation is accomplished via the naming of defaults, so that reference may be made to a default rule from within a theory. In an elaboration of the approach, we allow an ordered default theory where preference information is specified within a default theory. Here one may specify preferences that hold by default, in a particular context, or give preferences among preferences. In the approach, one essentially axiomatises how different orderings interact within a theory and need not rely on metatheoretic characterisations. As well, we can immediately use existing default logic theorem provers for an implementation. From a theoretical point of view, this shows that the explicit representation of priorities among defaults adds nothing to the overall expressibility of default logic.

In this paper we consider a logical treatment for the ordered disjunction operator × introduced by Brewka, Niemelä and Syrjänen in their Logic Programs with Ordered Disjunctions (LPOD). LPODs are used to represent preferences in logic programming under the answer set semantics. Their semantics is defined by first translating the LPOD into a set of normal programs (called split programs) and then imposing a preference relation among the answer sets of these split programs. We concentrate on the first step and show how a suitable translation of the ordered disjunction as a derived operator into the logic of Here-and-There allows capturing the answer sets of the split programs in a direct way. We use this characterisation not only for providing an alternative implementation for LPODs, but also for checking several properties (under strongly equivalent transformations) of the × operator, like for instance, its distributivity with respect to conjunction or regular disjunction. We also make a comparison to an extension proposed by Kärger, Lopes, Olmedilla and Polleres, that combines × with regular disjunction.

Possibility theory offers a qualitative framework for modeling decision under uncertainty. In this setting, pessimistic and optimistic decision criteria have been formally justified. The computation by means of possibilistic logic inference of optimal decisions according to such criteria has been proposed. This paper presents an Answer Set Programming (ASP)-based methodology for modeling decision problems and computing optimal decisions in the sense of the possibilistic criteria. This is achieved by applying both a classic and a possibilistic ASP-based methodology in order to handle both a knowledge base pervaded with uncertainty and a prioritized preference base.

In this paper, we show how the formalism of Logic Programs with Ordered Disjunction (LPODs) and Possibilistic Answer Set Programming (PASP) can be merged into the single framework of Logic Programs with Possibilistic Ordered Disjunction (LPPODs). The LPPODs framework embeds in a unified way several aspects of common-sense reasoning, nonmonotonocity, preferences, and uncertainty, where each part is underpinned by a well established formalism. On one hand, from LPODs it inherits the distinctive feature of expressing context-dependent qualitative preferences among different alternatives (modeled as the atoms of a logic program). On the other hand, PASP allows for qualitative certainty statements about the rules themselves (modeled as necessity values according to possibilistic logic) to be captured. In this way, the LPPODs framework supports a reasoning which is nonmonotonic, preference-and uncertainty-aware. The LPPODs syntax allows for the specification 1) preferences among the exceptions to default rules, and 2) necessity values about the certainty of program rules. As a result, preferences and uncertainty can be used to select the preferred uncertain default rules of an LPPODs and, consequently, to order its possibilistic answer sets. Furthermore, we describe the implementation of an ASP-based solver able to compute the LPPODs semantics.

In this paper we define a class of nested logic programs, nested logic programs with ordered disjunction (LPODs+), which allows to specify qualitative preferences by means of nested preference expressions. For doing this we extend the syntax of logic programs with ordered disjunction (LPODs) to capture more general expressions. We define the LPODs+ semantics in a simple way and we extend most of the results of logic programs with ordered disjunction showing how our approach effectively is a proper generalisation of LPODs.

We introduce the class of possibilistic nested logic programs. These possibilistic logic programs allow us to use nested expressions in the bodies and the heads of their rules. By considering a possibilistic nested logic program as a possibilistic theory, a construction of a possibilistic logic programing semantics based on answer sets for nested logic programs and the proof theory of possibilistic logic is defined. We show that this new semantics for possibilistic logic programs is computable by means of transforming possibilistic nested logic programs into possibilistic disjunctive logic programs. The expressiveness of the possibilistic nested logic programs is illustrated by scenarios from the medical domain. In particular, we exemplify how possibilistic nested logic programs are expressive enough for capturing medical guidelines which are pervaded of vagueness and qualitative information.

Abstract. Normal Form Nested (NFN) programs have recently been introduced in order to allow for enriching the syntax of disjunctive logic programs under the answer sets semantics. In particular, heads of rules can be disjunctions of con-junctions, while bodies can be conjunctions of disjunctions. Different to many other proposals of this kind, NFN programs may contain variables, and a no-tion of safety has been defined for guaranteeing domain independence. More-over, NFN programs can be efficiently translated to standard disjunctive logic programs (DLP). In this paper we present the tool nfn2dlp, a compiler for NFN programs, which implements an efficient translation from safe NFN programs to safe DLP pro-grams. The answer sets of the original NFN program can be obtained from the answer sets of the transformed program (which in turn can be obtained by using a DLP system) by a simple transformation. The system has been implemented using the object-oriented programming language Ruby an...

Our goal is to derive bottom-up query-evaluation algorithms from abstract properties of the underlying negation semantics. In this paper, we demonstrate our approach for the disjunctive stable model semantics, but the ideas are applicable to many other semantics as well. Our framework also helps to understand and compare other proposed query evaluation algorithms. It is based on the notion of conditional facts, developed by Bry and Dung/Kanchansut. We start by computing a \residual program" and show that it is equivalent to the original program under very general conditions on the semantics (which are satis ed, e.g., by the well-founded, stable, stationary, and static semantics). Many queries can already be answered on the basis of the residual program. For the remaining literals, we propose to use an appropriate completion of the residual program, which syntactically characterizes the intended models. In the case of the stable model semantics, we utilize an interesting connection to Clark's completion.

Normal Form Nested (NFN) programs have recently been introduced in order to allow for enriching the syntax of disjunctive logic programs under the answer sets semantics. In particular, heads of rules can be disjunctions of conjunctions, while bodies can be conjunctions of disjunctions. Different to many other proposals of this kind, NFN programs may contain variables, and a notion of safety has been defined for guaranteeing domain independence. Moreover, NFN programs can be efficiently translated to standard disjunctive logic programs (DLP). In this paper we present the tool nfn2dlp, a compiler for NFN programs, which implements an efficient translation from safe NFN programs to safe DLP programs. The answer sets of the original NFN program can be obtained from the answer sets of the transformed program (which in turn can be obtained by using a DLP system) by a simple transformation. The system has been implemented using the object-oriented programming language Ruby and Treetop, a l...

Normal Form Nested (NFN) programs have recently been introduced in order to allow for enriching the syntax of disjunctive logic programs under the answer sets semantics. In particular, heads of rules can be disjunctions of conjunctions, while bodies can be conjunctions of disjunctions. Different to many other proposals of this kind, NFN programs may contain variables, and a notion of safety has been defined for guaranteeing domain independence. Moreover, NFN programs can be efficiently translated to standard disjunctive logic programs (DLP). In this paper we present the tool nfn2dlp, a compiler for NFN programs, which implements an efficient translation from safe NFN programs to safe DLP programs. The answer sets of the original NFN program can be obtained from the answer sets of the transformed program (which in turn can be obtained by using a DLP system) by a simple transformation. The system has been implemented using the object-oriented programming language Ruby and Treetop, a language for Parsing Expression Grammars (PEGs). It currently produces DLP programs in the format of DLV. The separate script nfnsolve uses DLV as a back-end to compute answer sets for NFN programs. Thus, combining the two tools we obtain a system which supports the powerful NFN language, and is available for experiments.

In this paper we extend the Revision Programming framework-a logic-based framework to express and maintain constraints on knowledge baseswith different forms of preferences. Preferences allow users to introduce a bias in the way agents update their knowledge to meet a given set of constraints. In particular, they provide a way to select one between alternative feasible revisions and they allow for the generation of revisions in presence of conflicting constraints, by relaxing the set of satisfied constraints (soft constraints). A methodology for computing preferred revisions using answer set programming is presented. Revision rules also have a computational (imperative) interpretation that expresses a way to enforce a constraint. Assume that all data items , ½ Ñ, belong to the current database, say Á, and none of the data items , ½ Ò, belongs to Á. Then, to enforce the constraint (1), the item must be added to the database (removed from it, in the case of the constraint (2)), rather than removing (adding) some item ().

We introduce a flexible framework to specify problem so- lutions (outcomes) and preferences among them. The pro- posal combines ideas from answer-set programming (ASP), answer-set optimization (ASO) and CP-nets. The problem domain is structured into components. ASP techniques are used to specify values of components, as well as global (inter- component) constraints among these values. ASO methods are used to describe preferences among the values of a com- ponent and CP-net techniques to represent inter-component dependencies and corresponding preferences.

We present CR-Prolog ¾ , an extension of A-Prolog with crrules and ordered disjunction. CR-rules can be used to formalize various types of common-sense knowledge and reasoning, that, to the best of our knowledge, have no formalization in A-Prolog. The use of ordered disjunction often allows for a very concise, easy to read, representation of knowledge. We also show how CR-Prolog ¾ can be used to represent preferences intended both as strict preferences, and as desires.

We present CR-Prolog¾, an extension of CR-Prolog with an improved semantics, and allowing ordered disjunction in the head of both regular rules and consistency-restoring rules. The new semantics yields intuitive conclusions in cases when CR-Prolog would give unintuitive results. The use of ordered disjunction often allows for a more concise, easier to read, representation of knowledge. We also show how CR-Prolog¾ can be used to represent preferences intended both as strict preferences (like in CR-Prolog), and as desires (like in LPOD, where ordered disjunction was initially introduced). Finally, we show how the new language can be used to represent complex knowledge and to perform fairly sophisticated reasoning tasks.

Nested logic programs have recently been introduced in order to allow for arbitrarily nested formulas in the heads and the bodies of logic program rules under the answer sets semantics. Nested expressions can be formed using conjunction, disjunction, as well as the negation as failure operator in an unrestricted fashion. This provides a very flexible framework for knowledge representation and reasoning. Previous results show that nested logic programs can be transformed into standard (unnested) disjunctive logic programs in an elementary way, applying the negation as failure operator to body literals only. This is of great practical relevance since it allows us to evaluate nested logic programs by means of off-the-shelf disjunctive logic programming systems, like DLV. However, it turns out that this straightforward transformation results in an exponential blow-up in the worst-case, despite the fact that complexity results indicate that there is a polynomial translation among both formalisms. In this paper, we take up this challenge and provide polynomial translations of logic programs with nested expressions into disjunctive logic programs. Moreover, we show that these translations are modular and (strongly) faithful. We have implemented both the straightforward as well as our advanced transformations; the resulting compiler serves as a front-end to DLV and is publicly available on the Web. Finally, we also report experimental results, comparing the different translations on several classes of benchmark problems.

nlp is a compiler for nested logic programming under answer set semantics. It is designed as a front-end translating nested logic programs into disjunctive ones, whose answer sets are then computable by disjunctive logic programming systems, like dlv or gnt. nlp offers different translations: One is polynomial but necessitates the introduction of new atoms, another is exponential in the worst case but avoids extending the language. We report experimental results, comparing the translations on several classes of benchmark problems.

From 24.04.05 to 29.04.05, the Dagstuhl Seminar 05171 "Nonmonotonic Reasoning, Answer Set Programming and Constraints" was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.

We introduce a methodology and framework for expressing general preference information in logic programming,under the answer set semantics. An ordered logic program,is an extended logic program in which rules are named by unique terms, and in which preferences among,rules are given by a set of atoms of form s,t where s and t are names. An ordered logic program

Qualitative choice logic (QCL) is a propositional logic for representing alternative, ranked options for problem solutions. The logic adds to classical propositional logic a new connective called ordered disjunction: A × B intuitively means: if possible A, but if A is not possible then at least B. The semantics of qualitative choice logic is based on a preference relation among models. Consequences of QCL theories can be computed through a compilation to stratified knowledge bases which in turn can be compiled to classical propositional theories. We also discuss potential applications of the logic, several variants of QCL based on alternative inference relations, and their relation to existing nonmonotonic formalisms. 1

Reasoning about preferences is a major issue in many decision making problems. Recently, a new logic for handling preferences, called Qualitative Choice Logic (QCL), was presented. This logic adds to classical propositional logic a new connective, called ordered disjunction symbolized by ×. That new connective is used to express preferences between alternatives. QCL was not designed to handle conditional preferences, even if it is possible to express an implication with a preference on the left hand side, for instance "(Air France × Virgin) ⇒ Hotel Package". However, using QCL semantics, there is no difference between such material implication "(Virgin × Air France) ⇒ Hotel Package" and the purely propositional formula "(Air France ∨ Virgin) ⇒ Hotel Package ". Indeed, the negation in QCL gets rid of nested ordered disjunctions. Furthermore, the negation in QCL misses some desirable properties from propositional calculus. In this paper, we present a new semantics for the QCL language that addresses those problems. We describe a general framework for handling qualitative preferences. That framework is based on normal form functions that transform general QCL formulas into basic choice formulas, which are simple formulas (ordered disjunction of propositional formulas). We formulate the properties of our normal form function that overcome current QCL limitations.

In this paper we extend the Revision Programming framework—a logic-based framework to express and maintain constraints on knowledge bases— with different forms of preferences. Preferences allow users to introduce a bias in the way agents update their knowledge to meet a given set of constraints. In par- ticular, they provide a way to select one between alternative feasible revisions and they allow for the generation of revisions in presence of conflicting constraints, by relaxing the set of satisfied constraints ( soft constraints). A methodology for computing preferred revisions using answer set programming is presented.

We investigate the combination of answer set pro­ gramming and qualitative optimization techniques. Answer set optimization programs (ASO pro­ grams) have two parts. The generating program produces answer sets representing possible solutions. The preference program expresses user preferences. It induces a preference relation on the answer sets of based on the degree to which rules are satisfied. We discuss possible

We introduce a flexible framework to specify problem so- lutions (outcomes) and preferences among them. The pro- posal combines ideas from answer-set programming (ASP), answer-set optimization (ASO) and CP-nets. The problem domain is structured into components. ASP techniques are used to specify values of components, as well as global (inter- component) constraints among these values. ASO methods are used to describe preferences among the values of a com- ponent and CP-net techniques to represent inter-component dependencies and corresponding preferences.

Possibility theory offers a qualitative framework for modeling decision under uncertainty. In this setting, pessimistic and optimistic decision criteria have been formally justified. The computation by means of possibilistic logic inference of optimal decisions according to such criteria has been proposed. This paper presents an Answer Set Programming (ASP)-based methodology for modeling decision problems and computing optimal decisions in the sense of the possibilistic criteria. This is achieved by applying both a classic and a possibilistic ASP-based methodology in order to handle both a knowledge base pervaded with uncertainty and a prioritized preference base.

In this paper, we show how the formalism of Logic Programs with Ordered Disjunction (LPODs) and Possibilistic Answer Set Programming (PASP) can be merged into the single framework of Logic Programs with Possibilistic Ordered Disjunction (LPPODs). The LPPODs framework embeds in a unified way several aspects of common-sense reasoning, nonmonotonocity, preferences, and uncertainty, where each part is underpinned by a well established formalism. On one hand, from LPODs it inherits the distinctive feature of expressing context-dependent qualitative preferences among different alternatives (modeled as the atoms of a logic program). On the other hand, PASP allows for qualitative certainty statements about the rules themselves (modeled as necessity values according to possibilistic logic) to be captured. In this way, the LPPODs framework supports a reasoning which is nonmonotonic, preference-and uncertainty-aware. The LPPODs syntax allows for the specification of (1) preferences among the exceptions to default rules, and (2) necessity values about the certainty of program rules. As a result, preferences and R. Confalonieri (R. Confalonieri et al. uncertainty can be used to select the preferred uncertain default rules of an LPPOD and, consequently, to order its possibilistic answer sets. Furthermore, we describe the implementation of an ASP-based solver able to compute the LPPODs semantics.

In this paper we define a class of nested logic programs, nested logic programs with ordered disjunction (LPODs+), which allows to specify qualitative preferences by means of nested preference expressions. For doing this we extend the syntax of logic programs with ordered disjunction (LPODs) to capture more general expressions. We define the LPODs+ semantics in a simple way and we extend most of the results of logic programs with ordered disjunction showing how our approach effectively is a proper generalisation of LPODs.

This paper presents an approach for specifying user preferences related to services by means of a preference meta-model, which is mapped to logic programs with possibilistic ordered disjunction following a Model-Driven Methodology (MDM). MDM allows to specify problem domains by means of meta-models which can be converted to instance models or other meta-models through transformation functions. In particular we propose a preference meta-model that defines an abstract preference specification language allowing users to ...

Preferences are useful when the space of feasible solutions of a given problem is dense but not all these solutions are equivalent w.r.t. some additional requirements. In this case, the goal is to find feasible solutions that most satisfy these additional requirements. In order to represent preferences, in this paper we use an extension of ordered disjunction programs. Ordered disjunction is an approach based on answer sets that allows us to represent alternative, ranked options for a problem. Moreover, we give a brief overview of two real applications of extended ordered programs in two different domains. The first one is in planning: evacuation planning. The second one is in argumentation: organ transplantation. In particular, we show the role of negated negative literals in extended ordered programs to obtain the preferred solution of each application.

We equip ordered logic programs with negation as failure, using a simple generalization of the preferred answer set semantics for ordered programs. This extension supports a convenient formulation of certain problems, which is illustrated by means of an intuitive simulation of logic programming with ordered disjunction. The simulation also supports a broader application of "ordered disjunction", handling problems that would be cumbersome to express using ordered disjunction logic programs. Interestingly, allowing negation as failure in ordered logic programs does not yield any extra computational power: the combination of negation as failure and order can be simulated using order (and true negation) alone.

We extend answer set semantics to deal with inconsistent programs (containing classical negation), by finding a "best" answer set. Within the context of inconsistent programs, it is natural to have a partial order on rules, representing a preference for satisfying certain rules, possibly at the cost of violating less important ones. We show that such a rule order induces a natural order on extended answer sets, the minimal elements of which we call preferred answer sets. We characterize the expressiveness of the resulting semantics and show that it can simulate negation as failure, disjunction and some other formalisms such as logic programs with ordered disjunction. The approach is shown to be useful in several application areas, e.g. repairing database, where minimal repairs correspond to preferred answer sets. 5 of X that are not ordinary literals, i.e. X − = {l | not l ∈ X}. We say that X is consistent iff the set of ordinary literals ¬X − ∪ (X \not X − ) is consistent.

Answer Set Programming (ASP) is a popular framework for modeling combinatorial problems. However, ASP cannot easily be used for reasoning about uncertain information. Possibilistic ASP (PASP) is an extension of ASP that combines possibilistic logic and ASP. In PASP a weight is associated with each rule, where this weight is interpreted as the certainty with which the conclusion can be established when the body is known to hold. As such, it allows us to model and reason about uncertain information in an intuitive way. In this paper we present new semantics for PASP, in which rules are interpreted as constraints on possibility distributions. Special models of these constraints are then identified as possibilistic answer sets. In addition, since ASP is a special case of PASP in which all the rules are entirely certain, we obtain a new characterization of ASP in terms of constraints on possibility distributions. This allows us to uncover a new form of disjunction, called weak disjunction, that has not been previously considered in the literature. In addition to introducing and motivating the semantics of weak disjunction, we also pinpoint its computational complexity. In particular, while the complexity of most reasoning tasks coincides with standard disjunctive ASP, we find that brave reasoning for programs with weak disjunctions is easier.

Weight constraints are a powerful programming construct that has proved very useful within the Answer Set Programming paradigm. In this paper, we argue that practical Answer Set Programming might take profit from introducing some forms of nested weight constraints. We define such empowered constraints (that we call "Nested Weight Constraints") and discuss their semantics and their complexity.

Preferences are useful when the space of feasible solutions of a given problem is dense but not all these solutions are equivalent w.r.t. some additional requirements. In this case, the goal is to find feasible solut ions that most satisfy these additional requirements. In order to represent prefe rences, in this paper we use an extension of ordered disjunction programs.

We describe a system that provides what we call all things considered support to a user. The core feature of this system is that it finds a balance between the satisfaction of short term (local) preferences and the satisfaction of long term (global) preferences. By operating according to both local and global standards the system serves a debiasing function – it produces recommendations that bypass the common tendency that people have of granting excessive weight to utilities that relate to the short term. The novelty of this system is that for every decision it has to make it considers a user’s interests all things considered; it incorporates that user’s local interests as well as his global interests.

we propose a novel method for evaluating,

detecting, and inferring preferences in choice situations

involving items with multiple attributes. Our method locates

characteristics that reflect the relative weight that a user gives

to varying attributes belonging to an item, when these attributes

are combined into a unified multi-attribute utility function. Our

method enables the attainment of coefficients that reflect the

preferential prism of a user in relation to items with multiple

attributes. Broadly, we translate the form of a u-function into

an inequality with scalar variables which define half-spaces

on a plane. These half-spaces intersect and form closed shapes

(in a k-dimensional world). The closed shapes with the most

intersections are the most likely areas in which the vector lies.

Attaining the values of the various xi allow a computational

system to restore the u-function. This enables the system to

predict the alternative item’s total utilities in yet unmet choice-
making scenarios.

A novel extension of methods relates to the identification of

inconsistent choice-making. In addressing the latter problem,

we note that hyper-planes split the n-dimensional world into

parts. We relate to every one of these parts (segments or rays

in 1D, shapes, bounded or unbounded, in 2D), and count the

number of half-spaces that contain it; this number reflects

the probability that the actual (unknown) parameters are in it.

Counting the number of half-spaces containing each segment

allows us to consider multiple user profiles and considerations.

This paves the way to the construction of more complex

frameworks for understanding user choice as a multi-criteria

decision making problem.

In this paper we define a class of nested logic programs, nested logic programs with ordered disjunction (LPODs+), which allows to specify qualitative preferences by means of nested preference expressions. For doing this we extend the syntax of logic programs with ordered disjunction (LPODs) to capture more general expressions. We define the LPODs+ semantics in a simple way and we extend most of the results of logic programs with ordered disjunction showing how our approach effectively is a proper generalisation of LPODs.

This paper presents an approach for specifying user preferences related to services by means of a preference meta-model, which is mapped to logic programs with possibilistic ordered disjunction following a Model-Driven Methodology (MDM). MDM allows to specify problem domains by means of meta-models which can be converted to instance models or other meta-models through transformation functions.

Recommender system technology can present personalised offers to customers of companies. This technology suffers from the cold-start and sparsity problems. On the other hand, in most researches, less attention has been paid to user's preferences varieties in different product categories and also explicit and implicit attributes of products. Since users express their opinions implicitly based on some specific attributes of products, this paper proposes a hybrid recommendation approach based on attributes of products to address these problems. After product category and taxonomy formation and attributes extraction for each category, explicit-based module provides recommendations through naive Bayes classifier. Implicit-based module considers the weight vector of implicit attributes for users as chromosomes in genetic algorithm. This algorithm optimises the weights according to historical rating. Finally, recommendations are generated using the results of two modules. The main contributions are addressing sparsity and cold-start problem using naive Bayes classifier and weight optimisation by genetic algorithm.

In the context of Network management, Chomicki et al. defined the specification language PDL (Policy Description Language) and later extended it by introducing monitors: constraints on the actions that the network manager cannot execute simultaneously. We have furtherly extended PDL by permitting specifying user preferences on how to enforce constraints; that extension is called PPDL and it is based on Brewka's ordered disjunction connective. In this article we speculate on how the minimality requirement, stating that constraints on actions should affect action execution as little as possible, can be specified and implemented in PPDL theories. Minimal interference and maximal satisfaction of user preferences are not always achievable and tend to interact in complex ways. This work has been supported by i) MIUR COFIN project Aggregate-and numberreasoning for computing: from decision algorithms to constraint programming with multisets, sets, and maps. and ii) the Information Society Technologies programme of the European Commission, Future and Emerging Technologies under the IST-2001-37004 WASP and IST-2001-33058 PANDA projects.

In the context of Network management, Chomicki, Lobo and Naqvi have defined the specification language PDL (Policy Description Language) and later extended it by introducing monitors: constraints on the actions that the network manager can execute simultaneously. We believe that PDL may be of interest as a specification language for intelligent systems. This article proposes an extension of PDL that allows user-defined preferences on how to apply monitors. We adopt Brewka's approach to preference as in LPOD and show how his "×" ordered disjunction connective can be added to PDL. * Work supported by i) MIUR COFIN project Aggregate-and number-reasoning for computing: from decision algorithms to constraint programming with multisets, sets, and maps. and ii) the Information Society Technologies programme of the European Commission, Future and Emerging Technologies under the IST-2001-37004 WASP project. 2 We will not consider here the boolean condition C as it is not determinant for our argumentation.