Verification of Golog Programs over Description Logic Actions

High-level action programming languages such as Golog have successfully been used to model the behavior of autonomous agents. In addition to a logic-based action formalism for describing the environment and the effects of basic actions, they enable the construction of complex actions using typical programming language constructs. To ensure that the execution of such complex actions leads to the desired behavior of the agent, one needs to specify the required properties in a formal way, and then verify that these requirements are met by any execution of the program. Due to the expressiveness of the action formalism underlying Golog (situation calculus), the verification problem for Golog programs is in general undecidable. Action formalisms based on Description Logic (DL) try to achieve decidability of inference problems such as the projection problem by restricting the expressiveness of the underlying base logic. However, until now these formalisms have not been used within Golog programs. In the present paper, we introduce a variant of Golog where basic actions are defined using such a DL-based formalism, and show that the verification problem for such programs is decidable. This improves on our previous work on verifying properties of infinite sequences of DL actions in that it considers (finite and infinite) sequences of DL actions that correspond to (terminating and non-terminating) runs of a Golog program rather than just infinite sequences accepted by a Büchi automaton abstracting the program

Actions with Conjunctive Queries:: Projection, Conflict Detection and Verification

Description Logic actions specify adaptations of description logic interpretations based on some preconditions defined using a description logic. We consider DL actions in which preconditions can be specified using DL axioms as well as using conjunctive queries, and combinatiosn thereof. We investigate complexity bounds for the executability and the projection problem for these actions, which respectively ask whether an action can be executed on models of an interpretation, and which entailments are satisfied after an action has been executed on this model. In addition, we consider a set of new reasoning tasks concerned with conflicts and interactions that may arise if two action are executed at the same time. Since these problems have not been investigated before for Description Logic actions, we investigate the complexity of these tasks both for actions with conjunctive queries and without those. Finally, we consider the verification problem for Golog programs formulated over our famility of actions. Our complexity analysis considers several expressive DLs, and we provide tight complexity bounds for those for which the exact complexity of conjunctive query entailment is known

Agent programming in the cognitive era

It is claimed that, in the nascent ‘Cognitive Era’, intelligent systems will be trained using machine learning techniques rather than programmed by software developers. A contrary point of view argues that machine learning has limitations, and, taken in isolation, cannot form the basis of autonomous systems capable of intelligent behaviour in complex environments. In this paper, we explore the contributions that agent-oriented programming can make to the development of future intelligent systems. We briefly review the state of the art in agent programming, focussing particularly on BDI-based agent programming languages, and discuss previous work on integrating AI techniques (including machine learning) in agent-oriented programming. We argue that the unique strengths of BDI agent languages provide an ideal framework for integrating the wide range of AI capabilities necessary for progress towards the next-generation of intelligent systems. We identify a range of possible approaches to integrating AI into a BDI agent architecture. Some of these approaches, e.g., ‘AI as a service’, exploit immediate synergies between rapidly maturing AI techniques and agent programming, while others, e.g., ‘AI embedded into agents’ raise more fundamental research questions, and we sketch a programme of research directed towards identifying the most appropriate ways of integrating AI capabilities into agent programs

Verification of Golog Programs over Description Logic Actions

High-level action programming languages such as Golog have successfully been used to model the behavior of autonomous agents. In addition to a logic-based action formalism for describing the environment and the effects of basic actions, they enable the construction of complex actions using typical programming language constructs. To ensure that the execution of such complex actions leads to the desired behavior of the agent, one needs to specify the required properties in a formal way, and then verify that these requirements are met by any execution of the program. Due to the expressiveness of the action formalism underlying Golog (situation calculus), the verification problem for Golog programs is in general undecidable. Action formalisms based on Description Logic (DL) try to achieve decidability of inference problems such as the projection problem by restricting the expressiveness of the underlying base logic. However, until now these formalisms have not been used within Golog programs. In the present paper, we introduce a variant of Golog where basic actions are defined using such a DL-based formalism, and show that the verification problem for such programs is decidable. This improves on our previous work on verifying properties of infinite sequences of DL actions in that it considers (finite and infinite) sequences of DL actions that correspond to (terminating and non-terminating) runs of a Golog program rather than just infinite sequences accepted by a Büchi automaton abstracting the program

Verification of Golog Programs over Description Logic Actions

High-level action programming languages such as Golog have successfully been used to model the behavior of autonomous agents. In addition to a logic-based action formalism for describing the environment and the effects of basic actions, they enable the construction of complex actions using typical programming language constructs. To ensure that the execution of such complex actions leads to the desired behavior of the agent, one needs to specify the required properties in a formal way, and then verify that these requirements are met by any execution of the program. Due to the expressiveness of the action formalism underlying Golog (situation calculus), the verification problem for Golog programs is in general undecidable. Action formalisms based on Description Logic (DL) try to achieve decidability of inference problems such as the projection problem by restricting the expressiveness of the underlying base logic. However, until now these formalisms have not been used within Golog programs. In the present paper, we introduce a variant of Golog where basic actions are defined using such a DL-based formalism, and show that the verification problem for such programs is decidable. This improves on our previous work on verifying properties of infinite sequences of DL actions in that it considers (finite and infinite) sequences of DL actions that correspond to (terminating and non-terminating) runs of a Golog program rather than just infinite sequences accepted by a Büchi automaton abstracting the program

Verification of Golog Programs over Description Logic Actions

Golog is a powerful programming language for logic-based agents. The primitives of the language are actions whose preconditions and effects are defined in a Situation Calculus action theory using first-order logic. To describe possible courses of actions the programmer can freely combine imperative control structures with constructs for non-deterministic choice, leaving it to the system to resolve the non-determinism in a suitable manner. Golog has been successfully used for high-level decision making in the area of cognitive robotics. Obviously, it is important to verify certain properties of a Golog program before executing it on a physical robot. However, due to the high expressiveness of the language the verification problem is in general undecidable. In this thesis, we study the verification problem for Golog programs over actions defined in action languages based on Description Logics and explore the boundary between decidable and undecidable fragments

Environnement d'assistance au développement de transformations de graphes correctes

Les travaux de cette thèse ont pour cadre la vérification formelle, et plus spécifiquement le projet ANR Blanc CLIMT (Categorical and Logical Methods in Model Transformation) dédié aux grammaires de graphes. Ce projet, qui a démarré en février 2012 pour une durée de 48 mois, a donné lieu à la définition du langage Small-tALC, bâti sur la logique de description ALCQI. Ce langage prend la forme d’un DSL (Domain Specific Language) impératif à base de règles, chacune dérivant structurellement un graphe. Le langage s’accompagne d’un composant de preuve basé sur la logique de Hoare chargé d’automatiser le processus de vérification d’une règle. Cependant, force est de constater que tous les praticiens ne sont pas nécessairement familiers avec les méthodes formelles du génie logiciel et que les transformations sont complexes à écrire. En particulier, ne disposant que du seul prouveur, il s’agit pour le développeur Small-tALC d’écrire un triplet de Hoare {P} S {Q} et d’attendre le verdict de sa correction sous la forme d’un graphe contre-exemple en cas d’échec. Ce contre-exemple est parfois difficile à décrypter, et ne permet pas de localiser aisément l’erreur au sein du triplet. De plus, le prouveur ne valide qu’une seule règle à la fois, sans considérer l’ensemble des règles de transformation et leur ordonnancement d’exécution. Ce constat nous a conduits à proposer un environnement d’assistance au développeur Small-tALC. Cette assistance vise à l’aider à rédiger ses triplets et à prouver ses transformations, en lui offrant plus de rétroaction que le prouveur. Pour ce faire, les instructions du langage ont été revisitées selon l’angle ABox et TBox de la logique ALCQI. Ainsi, conformément aux logiques de description, la mise à jour du graphe par la règle s’assimile à la mise à jour ABox des individus (les nœuds) et de leurs relations (les arcs) d’un domaine terminologique TBox (le type des nœuds et les étiquettes des arcs) susceptible d’évoluer. Les contributions de cette thèse concernent : (1) un extracteur de préconditions ABox à partir d’un code de transformation S et de sa postcondition Q pour l’écriture d’une règle {P} S {Q} correcte par construction, (2) un raisonneur TBox capable d’inférer des propriétés sur des ensembles de nœuds transformés par un enchaînement de règles {Pi} Si {Qi}, et (3) d’autres diagnostics ABox et TBox sous la forme de tests afin d’identifier et de localiser des problèmes dans les programmes. L’analyse statique du code de transformation d’une règle, combinée à un calcul d’alias des variables désignant les nœuds du graphe, permet d’extraire un ensemble de préconditions ABox validant la règle. Les inférences TBox pour un enchaînement de règles résultent d’une analyse statique par interprétation abstraite des règles ABox afin de vérifier formellement des états du graphe avant et après les appels des règles. A ces deux outils formels s’ajoutent des analyseurs dynamiques produisant une batterie de tests pour une règle ABox, ou un diagnostic TBox pour une séquence de règle

Pseudo-contractions as Gentle Repairs

Updating a knowledge base to remove an unwanted consequence is a challenging task. Some of the original sentences must be either deleted or weakened in such a way that the sentence to be removed is no longer entailed by the resulting set. On the other hand, it is desirable that the existing knowledge be preserved as much as possible, minimising the loss of information. Several approaches to this problem can be found in the literature. In particular, when the knowledge is represented by an ontology, two different families of frameworks have been developed in the literature in the past decades with numerous ideas in common but with little interaction between the communities: applications of AGM-like Belief Change and justification-based Ontology Repair. In this paper, we investigate the relationship between pseudo-contraction operations and gentle repairs. Both aim to avoid the complete deletion of sentences when replacing them with weaker versions is enough to prevent the entailment of the unwanted formula. We show the correspondence between concepts on both sides and investigate under which conditions they are equivalent. Furthermore, we propose a unified notation for the two approaches, which might contribute to the integration of the two areas