Challenges in Bridging Social Semantics and Formal Semantics on the Web

This paper describes several results of Wimmics, a research lab which names stands for: web-instrumented man-machine interactions, communities, and semantics. The approaches introduced here rely on graph-oriented knowledge representation, reasoning and operationalization to model and support actors, actions and interactions in web-based epistemic communities. The re-search results are applied to support and foster interactions in online communities and manage their resources

The Unit Graphs Mathematical Framework

We are interested in the choice of a graph-based knowledge representation formalism that would allow for the representation, manipulation, query, and reasoning over linguistic knowledge of the Explanatory Combinatorial Dictionary (ECD) of the Meaning-Text Theory (MTT). We show that neither the semantic web formalisms nor the Conceptual Graphs Formalism are suitable for this task, and we justify the introduction of the new Unit Graphs (UGs) framework. We introduce the fundamental concepts of the UGs mathematical framework: the Unit Types hierarchy and the Unit Graphs. We then show how they may be used to represent lexicographic definitions in the ECD. Finally we provide the UGs with reasoning capabilities.Nous nous intéressons au choix d'un formalisme de représentation des connaissances à base de graphes qui permette de représenter, manipuler, interroger et raisonner sur des connaissances linguistiques du Dictionnaire Explicatif et Combinatoire (DEC) de la Théorie Sens-Texte. Nous montrons que ni les formalismes du web sémantique ni le formalisme des Graphes conceptuels (GC) n'est adapté pour cela, et justifions l'introduction d'un nouveau formalisme dit des Graphes d'Unités. Nous introduisons donc les concepts fondamentaux du formalisme des Graphes d'Unités (GU): la hiérarchie des Types d'Unités et les Graphes d'Unités. Nous montrons ensuite comment on peut les utiliser pour représenter les définitions lexicographiques dans le DEC. Nous permettons finalement le raisonnement dans les GU

The Unit Graphs Mathematical Framework

We are interested in the choice of a graph-based knowledge representation formalism that would allow for the representation, manipulation, query, and reasoning over linguistic knowledge of the Explanatory Combinatorial Dictionary (ECD) of the Meaning-Text Theory (MTT). We show that neither the semantic web formalisms nor the Conceptual Graphs Formalism are suitable for this task, and we justify the introduction of the new Unit Graphs (UGs) framework. We introduce the fundamental concepts of the UGs mathematical framework: the Unit Types hierarchy and the Unit Graphs. We then show how they may be used to represent lexicographic definitions in the ECD. Finally we provide the UGs with reasoning capabilities.Nous nous intéressons au choix d'un formalisme de représentation des connaissances à base de graphes qui permette de représenter, manipuler, interroger et raisonner sur des connaissances linguistiques du Dictionnaire Explicatif et Combinatoire (DEC) de la Théorie Sens-Texte. Nous montrons que ni les formalismes du web sémantique ni le formalisme des Graphes conceptuels (GC) n'est adapté pour cela, et justifions l'introduction d'un nouveau formalisme dit des Graphes d'Unités. Nous introduisons donc les concepts fondamentaux du formalisme des Graphes d'Unités (GU): la hiérarchie des Types d'Unités et les Graphes d'Unités. Nous montrons ensuite comment on peut les utiliser pour représenter les définitions lexicographiques dans le DEC. Nous permettons finalement le raisonnement dans les GU

The use of data-mining for the automatic formation of tactics

This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques

The Unit Graphs Framework: A new graph-based Knowledge Representation Formalism for ECD Knowledge Representation

International audienceIn this paper we are interested in the choice of a graph-based knowledge representation formalism that would allow for the representation, manipulation, query, and reasoning over linguistic knowledge of the Explanatory Combinatorial Dictionary of the Meaning-Text Theory (MTT). We show that neither the semantic web formalisms nor the Conceptual Graphs Formalism are suitable for this task, and we justify the introduction of the new Unit Graphs framework. We then detail the core of this formalism which is a hierarchy of unit types driven by their actantial structure. Finally we define the new deep semantic representation level for the MTT, where the specialization of actantial structures of deep semantic unit types may correspond to a specialization of conveyed meanings

On the Complexity of the Tiden-Arnborg Algorithm for Unification modulo One-Sided Distributivity

We prove that the Tiden and Arnborg algorithm for equational unification modulo one-sided distributivity is not polynomial time bounded as previously thought. A set of counterexamples is developed that demonstrates that the algorithm goes through exponentially many steps.Comment: In Proceedings UNIF 2010, arXiv:1012.455

Extensional and Intensional Strategies

This paper is a contribution to the theoretical foundations of strategies. We first present a general definition of abstract strategies which is extensional in the sense that a strategy is defined explicitly as a set of derivations of an abstract reduction system. We then move to a more intensional definition supporting the abstract view but more operational in the sense that it describes a means for determining such a set. We characterize the class of extensional strategies that can be defined intensionally. We also give some hints towards a logical characterization of intensional strategies and propose a few challenging perspectives

Méthodologie d'ingénierie des connaissances pour la représentation des définitions lexicographiques dans le cadre de la théorie Sens-Texte

International audienceThe Meaning-Text Theory (MTT) is one of the most precise and exhaustive linguistic theories. Representing knowledge of the MTT is a challenge for applications in lexicography, but also for injecting fine grained linguistic knowledge in NLP systems. This paper describes the methodology and the main outcomes of our research in conducing a Knowledge Engineering approach to model the lexical knowledge of the MTT and formalize its semantics. We focus more specifically on linguistic predicates, linguistic representations, and lexicographic definitions. We drew our inspiration from Bachimont's methodology, and operated in three main steps: (i) we extended the domain conceptualization, (ii) we chose an adequate Knowledge Representation formalism, and (iii) we operationalized the formalism for logical reasoning, and for sharing and querying knowledge on the web of data.La Théorie Sens-Texte (TST) est l'une des théories linguistiques les plus précises d'un point de vue descriptif. En représenter les connaissances est un défi pour des applications de lexicographie, mais également pour injecter des connaissances linguistiques fines dans les systèmes de TALN. Cet article décrit la méthodologie et les principaux résultats de notre recherche qui consiste à mener une étude d'Ingénierie des Connaissances pour modéliser les connaissances lexicales sémantiques de la TST et en formaliser la sémantique. Nous nous intéressons plus particulièrement aux prédicats linguistiques, aux représentations linguistiques, et aux définitions lexicographiques. Nous nous sommes inspirés de la méthodologie de Bachimont, et avons opéré en trois étapes principales: (i) extension de la conceptualisation du domaine, (ii) recherche d'un formalisme de représentation des connaissances adapté, (iii) opérationalisation du formalisme pour le raisonnement logique et pour le partage et l'interrogation des connaissances sur le web des données

Abstractions in Reasoning for Long-Term Autonomy

The path to building adaptive, robust, intelligent agents has led researchers to develop a suite of powerful models and algorithms for agents with a single objective. However, in recent years, attempts to use this monolithic approach to solve an ever-expanding set of complex real-world problems, which increasingly include long-term autonomous deployments, have illuminated challenges in its ability to scale. Consequently, a fragmented collection of hierarchical and multi-objective models were developed. This trend continues into the algorithms as well, as each approximates an optimal solution in a different manner for scalability. These models and algorithms represent an attempt to solve pieces of an overarching problem: how can an agent explicitly model and integrate the necessary aspects of reasoning required to achieve long-term autonomy? This thesis presents a general hierarchical and multi-objective model called a policy network that unifies prior fragmented solutions into a single graphical decision-making structure. Policy networks are broadly useful to solve numerous real-world problems. This thesis focuses on autonomous vehicle (AV) problems: (1) route-planning with multiple objectives; (2) semi-autonomy with proactive transfer of control; and (3) intersection decision-making for reasoning online about any number of other vehicles and pedestrians. Formal models are presented for each of the distinct problems. Solutions are evaluated using real-world map data in simulation and demonstrated on a fully operational AV prototype driving on real public roads. Policy networks serve as a shared underlying framework for all three, enabling their seamless integration as parts of an overall solution for rich, real-world, scalable decision-making in agents with long-term autonomy