Preferential theory revision

AbstractEmploying a logic program approach, this paper focuses on applying preferential reasoning to theory revision, both by means of preferences among existing theory rules, and by means of preferences on the possible abductive extensions to the theory. And, in particular, how to prefer among plausible abductive explanations justifying observations

A creativity support system based on causal mapping.

Theory development is a very complex process that requires creativity and highly specialized analytical skills. This article presents a new algorithm, based on causal mapping, for assisting in the creation of qualitative theories. This algorithm is able to conjecture and prove new theorems, to test for consistency and completeness of the theory, and to derive meta-theorems comparing the different concepts in it. The use of the algorithm is exemplified in developing a theory to explain structural inertia in organizations

Machine ethics via logic programming

Machine ethics is an interdisciplinary field of inquiry that emerges from the need of imbuing autonomous agents with the capacity of moral decision-making. While some approaches provide implementations in Logic Programming (LP) systems, they have not exploited LP-based reasoning features that appear essential for moral reasoning. This PhD thesis aims at investigating further the appropriateness of LP, notably a combination of LP-based reasoning features, including techniques available in LP systems, to machine ethics. Moral facets, as studied in moral philosophy and psychology, that are amenable to computational modeling are identified, and mapped to appropriate LP concepts for representing and reasoning about them. The main contributions of the thesis are twofold. First, novel approaches are proposed for employing tabling in contextual abduction and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets. Second, a variety of LP-based reasoning features are applied to model the identified moral facets, through moral examples taken off-the-shelf from the morality literature. These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.Fundação para a Ciência e a Tecnologia (FCT)-grant SFRH/BD/72795/2010 ; CENTRIA and DI/FCT/UNL for the supplementary fundin

Every normal logic program has a 2-valued semantics: theory, extensions, applications, implementations

Trabalho apresentado no âmbito do Doutoramento em Informática, como requisito parcial para obtenção do grau de Doutor em InformáticaAfter a very brief introduction to the general subject of Knowledge Representation and Reasoning with Logic Programs we analyse the syntactic structure of a logic program and how it can influence the semantics. We outline the important properties of a 2-valued semantics for Normal Logic Programs, proceed to define the new Minimal Hypotheses semantics with those properties and explore how it can be used to benefit some knowledge representation and reasoning mechanisms. The main original contributions of this work, whose connections will be detailed in the sequel, are: • The Layering for generic graphs which we then apply to NLPs yielding the Rule Layering and Atom Layering — a generalization of the stratification notion; • The Full shifting transformation of Disjunctive Logic Programs into (highly nonstratified)NLPs; • The Layer Support — a generalization of the classical notion of support; • The Brave Relevance and Brave Cautious Monotony properties of a 2-valued semantics; • The notions of Relevant Partial Knowledge Answer to a Query and Locally Consistent Relevant Partial Knowledge Answer to a Query; • The Layer-Decomposable Semantics family — the family of semantics that reflect the above mentioned Layerings; • The Approved Models argumentation approach to semantics; • The Minimal Hypotheses 2-valued semantics for NLP — a member of the Layer-Decomposable Semantics family rooted on a minimization of positive hypotheses assumption approach; • The definition and implementation of the Answer Completion mechanism in XSB Prolog — an essential component to ensure XSB’s WAM full compliance with the Well-Founded Semantics; • The definition of the Inspection Points mechanism for Abductive Logic Programs;• An implementation of the Inspection Points workings within the Abdual system [21] We recommend reading the chapters in this thesis in the sequence they appear. However, if the reader is not interested in all the subjects, or is more keen on some topics rather than others, we provide alternative reading paths as shown below. 1-2-3-4-5-6-7-8-9-12 Definition of the Layer-Decomposable Semantics family and the Minimal Hypotheses semantics (1 and 2 are optional) 3-6-7-8-10-11-12 All main contributions – assumes the reader is familiarized with logic programming topics 3-4-5-10-11-12 Focus on abductive reasoning and applications.FCT-MCTES (Fundação para a Ciência e Tecnologia do Ministério da Ciência,Tecnologia e Ensino Superior)- (no. SFRH/BD/28761/2006

Λογικός προγραμματισμός με προτιμήσεις στην απειρότιμη λογική

Στην παρούσα διπλωματική εργασία προτείνουμε μια νέα επέκταση του λογικού προγραμματισμού. Αρχικά, εισάγουμε δύο τελεστές προτίμησης με τη σημασία «προαιρετικά» και «εναλλακτικά» αντίστοιχα, που μπορούν να εμφανίζονται στα σώματα των κανόνων και στη συνέχεια ορίζουμε σημασιολογία σταθερού σημείου για τη νέα αυτή γλώσσα. Η σημασιολογία βασίζεται στην απειρότιμη λογική, μια επέκταση της κλασικής δίτιμης λογικής στην οποία χρησιμοποιούνται άπειρες τιμές αλήθειας «λιγότερο αληθείς» από την τιμή T και άπειρες τιμές αλήθειας «λιγότερο ψευδείς» από την τιμή F . Η διαβάθμιση αυτή στις τιμές αληθείας αντιστοιχεί στον βαθμό προτίμησης.In this thesis we propose a new extension of Logic Programming. We introduce two unary preference operators with the meaning “optionally” and “alternatively” respectively, which can occur in the bodies of the clauses. In addition, we dene xed-point semantics for this new language. The semantics is based on Innitesimal Logic, an extension of classical two-valued logic, in which there are innite truth values that are “less true” than “standard” truth, and innite truth values that are “less false” than “standard” falsity. These dierent levels of truth values correspond to dierent degrees of preferences

Extensions of Logic Programming for Preference Representation

Εξετάζουμε το πρόβλημα της αναπαράστασης προτιμήσεων με τη χρήση επεκτάσεων του λογικού προγραμματισμού. Η αποτελεσματική αναπαράσταση προτιμήσεων είναι ζωτικής σημασίας σε πολλά επιστημονικά πεδία και μπορεί να αποδειχθεί χρήσιμη σε πολλές πραγματικές εφαρμογές. Οι φορμαλισμοί αναπαράστασης προτιμήσεων στη βιβλιογραφία συνήθως εμπίπτουν σε δύο βασικές κατηγορίες: στην ποιοτική προσέγγιση (όπου οι προτιμήσεις εκφράζονται με διμερείς σχέσεις προτίμησης) και στην ποσοτική προσέγγιση (όπου οι προτιμήσεις αναπαριστώνται με τη χρήση αριθμητικών τιμών που εκφράζουν το βαθμό ενδιαφέροντος). Σε αυτή τη διατριβή, προτείνουμε δύο προσεγγίσεις για την έκφραση προτιμήσεων. Η πρώτη προσέγγιση χρησιμοποιεί μια απειρότιμη επέκταση του λογικού προγραμματισμού για την έκφραση ποσοτικών προτιμήσεων, ενώ η δεύτερη προσέγγιση χρησιμοποιεί τον λογικό προγραμματισμό υψηλής τάξης για την έκφραση ποιοτικών προτιμήσεων. Προτείνουμε τη γλώσσα προγραμματισμού PrefLog, μια επέκταση του λογικού προγραμματισμού που χρησιμοποιεί ένα άπειρο σύνολο τιμών αλήθειας για να υποστηρίξει τον ορισμό τελεστών ποσοτικής προτίμησης. Ορίζουμε το συντακτικό και τη σημασιολογία της γλώσσας και προσδιορίζουμε ένα σύνολο από ιδιότητες τις οποίες πρέπει να ικανοποιούν οι διαθέσιμοι τελεστές προτίμησης έτσι ώστε η γλώσσα να έχει καλώς ορισμένη σημασιολογία. Επιπλέον, προτείνουμε μία «από-κάτω-προς-τα-πάνω» τεχνική υλοποίησης για ένα καλώς ορισμένο υποσύνολο της PrefLog που αντιστοιχεί στο προτιμησιακό αντίστοιχο της γλώσσας Datalog. Η εξασφάλιση της ιδιότητας του τερματισμού μιας τέτοιας στρατηγικής δεν είναι προφανής γιατί το σύνολο των τιμών αληθείας και το σύνολο των πιθανών ερμηνειών για τέτοια προγράμματα είναι και τα δύο άπειρα. Προτείνουμε τη χρήση του λογικού προγραμματισμού υψηλής τάξης για την αναπαράσταση ποιοτικών προτιμήσεων. Σε αυτήν την προσέγγιση, σχέσεις, προτιμήσεις μεταξύ πλειάδων, προτιμήσεις μεταξύ συνόλων από πλειάδες και υπολογισμοί σχετικά με προτιμήσεις εκφράζονται στην ίδια γλώσσα υψηλής τάξης. Τα προγράμματα αυτά μπορούν να εκτελεστούν σε πραγματικά συστήματα λογικού προγραμματισμού υψηλής τάξης και η απόδοσή τους μπορεί να ενισχυθεί είτε με γενικές είτε με εξειδικευμένες τεχνικές βελτιστοποίησης. Ανάμεσα σε αυτές, προτείνουμε μια νέα τεχνική μετατροπής λογικών προγραμμάτων υψηλής τάξης σε κλασικά λογικά προγράμματα (πρώτης τάξης) και την εφαρμόζουμε στα προγράμματα της προσέγγισής μας. Τέλος, αποδεικνύουμε την εφαρμοσιμότητα της προσέγγισής μας παρουσιάζοντας μια υλοποίηση και μια πειραματική αξιολόγηση στη γλώσσα λογικού προγραμματισμού υψηλής τάξης HiLog.We consider the problem of preference representation using extensions of logic programming. The effective representation of preferences is crucial in many scientific disciplines and it can be proven useful in many real-world applications. Preference representation formalisms in the literature usually fall into two basic categories: in the qualitative approach (where preferences are expressed with binary preference relations) and in the quantitative approach (where preferences are represented with the use of numerical values that express the degree of interest). In this dissertation, we propose two approaches for expressing preferences. The first approach uses an infinite-valued extension of logic programming for expressing quantitative preferences, while the second approach uses higher-order logic programming for expressing qualitative preferences. We propose PrefLog, a logic programming language which uses an underlying infinite-valued truth domain in order to support quantitative preference operators. We introduce the syntax and the semantics of the language, and we study the properties of the PrefLog operators that are needed in order for programs to behave well from a semantic point of view. In addition, we introduce a terminating bottom-up evaluation method for a well-defined class of function-free PrefLog programs. Ensuring termination is not a straightforward task, because the underlying truth domain of PrefLog and the set of all possible interpretations of a function-free PrefLog program are both infinite. We propose the use of higher-order logic programming as a framework for representing qualitative preferences. In this approach, relations, preferences between tuples, preferences between sets of tuples and operations on preferences are expressed in the same, higher-order language. The programs can be evaluated by standard higher-order programming systems, and their performance can be enhanced with generic and specialized optimization techniques. Among these techniques, we propose a novel program transformation technique for translating higher-order programs into first-order ones and we use this technique for optimizing the higher-order programs of our interest. Finally, we demonstrate the feasibility of our approach by presenting an implementation and an experimental evaluation of all the proposed concepts in the higher-order logic programming language HiLog

Preferential theory revision

Abstract. Employing a logic program approach, this paper focuses on applying preferential reasoning to theory revision, both by means of preferences among existing theory rules, and by means of preferences on the possible abductive extensions to the theory. And, in particular, how to prefer among plausible abductive explanations justifying observations.

Prospective Updating of Theories with Preferences

This work focuses on updating and revising theories with preferences within the context of logic programming. This aim is achieved by first exploiting preferences to reduce the number of abductive extensions of the initial theory, then by using the observations to confirm or deny the abduced hypotheses. In case the observations disconfirm the preferred abduced hypotheses, a revision process is launched in order to revise the theory’s preferences with respect to the new acquired observations. A methodology for model-based diagnosis is also proffered as an application of preferential theory revision, using observations to disambiguate among possible relevant revision scenarios. 1