444 research outputs found
Simulation and statistical model-checking of logic-based multi-agent system models
This thesis presents SALMA (Simulation and Analysis of Logic-Based Multi-
Agent Models), a new approach for simulation and statistical model checking
of multi-agent system models.
Statistical model checking is a relatively new branch of model-based approximative
verification methods that help to overcome the well-known scalability
problems of exact model checking. In contrast to existing solutions,
SALMA specifies the mechanisms of the simulated system by means of logical
axioms based upon the well-established situation calculus. Leveraging
the resulting first-order logic structure of the system model, the simulation
is coupled with a statistical model-checker that uses a first-order variant of
time-bounded linear temporal logic (LTL) for describing properties. This is
combined with a procedural and process-based language for describing agent
behavior. Together, these parts create a very expressive framework for modeling
and verification that allows direct fine-grained reasoning about the agents’
interaction with each other and with their (physical) environment.
SALMA extends the classical situation calculus and linear temporal logic
(LTL) with means to address the specific requirements of multi-agent simulation
models. In particular, cyber-physical domains are considered where
the agents interact with their physical environment. Among other things,
the thesis describes a generic situation calculus axiomatization that encompasses
sensing and information transfer in multi agent systems, for instance
sensor measurements or inter-agent messages. The proposed model explicitly
accounts for real-time constraints and stochastic effects that are inevitable in
cyber-physical systems.
In order to make SALMA’s statistical model checking facilities usable also
for more complex problems, a mechanism for the efficient on-the-fly evaluation
of first-order LTL properties was developed. In particular, the presented algorithm
uses an interval-based representation of the formula evaluation state
together with several other optimization techniques to avoid unnecessary computation.
Altogether, the goal of this thesis was to create an approach for simulation
and statistical model checking of multi-agent systems that builds upon
well-proven logical and statistical foundations, but at the same time takes a
pragmatic software engineering perspective that considers factors like usability,
scalability, and extensibility. In fact, experience gained during several small
to mid-sized experiments that are presented in this thesis suggest that the
SALMA approach seems to be able to live up to these expectations.In dieser Dissertation wird SALMA (Simulation and Analysis of Logic-Based
Multi-Agent Models) vorgestellt, ein im Rahmen dieser Arbeit entwickelter
Ansatz für die Simulation und die statistische Modellprüfung (Model Checking)
von Multiagentensystemen.
Der Begriff „Statistisches Model Checking” beschreibt modellbasierte approximative
Verifikationsmethoden, die insbesondere dazu eingesetzt werden
können, um den unvermeidlichen Skalierbarkeitsproblemen von exakten Methoden
zu entgehen. Im Gegensatz zu bisherigen Ansätzen werden in SALMA die
Mechanismen des simulierten Systems mithilfe logischer Axiome beschrieben,
die auf dem etablierten Situationskalkül aufbauen. Die dadurch entstehende
prädikatenlogische Struktur des Systemmodells wird ausgenutzt um ein Model
Checking Modul zu integrieren, das seinerseits eine prädikatenlogische Variante
der linearen temporalen Logik (LTL) verwendet. In Kombination mit
einer prozeduralen und prozessorientierten Sprache für die Beschreibung von
Agentenverhalten entsteht eine ausdrucksstarke und flexible Plattform für die
Modellierung und Verifikation von Multiagentensystemen. Sie ermöglicht eine
direkte und feingranulare Beschreibung der Interaktionen sowohl zwischen
Agenten als auch von Agenten mit ihrer (physischen) Umgebung.
SALMA erweitert den klassischen Situationskalkül und die lineare temporale
Logik (LTL) um Elemente und Konzepte, die auf die spezifischen Anforderungen
bei der Simulation und Modellierung von Multiagentensystemen
ausgelegt sind. Insbesondere werden cyber-physische Systeme (CPS) unterstützt,
in denen Agenten mit ihrer physischen Umgebung interagieren. Unter
anderem wird eine generische, auf dem Situationskalkül basierende, Axiomatisierung
von Prozessen beschrieben, in denen Informationen innerhalb von
Multiagentensystemen transferiert werden – beispielsweise in Form von Sensor-
Messwerten oder Netzwerkpaketen. Dabei werden ausdrücklich die unvermeidbaren
stochastischen Effekte und Echtzeitanforderungen in cyber-physischen
Systemen berücksichtigt.
Um statistisches Model Checking mit SALMA auch für komplexere Problemstellungen
zu ermöglichen, wurde ein Mechanismus für die effiziente Auswertung
von prädikatenlogischen LTL-Formeln entwickelt. Insbesondere beinhaltet
der vorgestellte Algorithmus eine Intervall-basierte Repräsentation des
Auswertungszustands, sowie einige andere Optimierungsansätze zur Vermeidung
von unnötigen Berechnungsschritten.
Insgesamt war es das Ziel dieser Dissertation, eine Lösung für Simulation
und statistisches Model Checking zu schaffen, die einerseits auf fundierten
logischen und statistischen Grundlagen aufbaut, auf der anderen Seite jedoch
auch pragmatischen Gesichtspunkten wie Benutzbarkeit oder Erweiterbarkeit
genügt. Tatsächlich legen erste Ergebnisse und Erfahrungen aus
mehreren kleinen bis mittelgroßen Experimenten nahe, dass SALMA diesen
Zielen gerecht wird
FLACOS’08 Workshop proceedings
The 2nd Workshop on Formal Languages and Analysis of Contract-Oriented Software (FLACOS’08) is held in Malta. The aim of the workshop is to bring together researchers and practitioners working on language-based solutions to contract-oriented software development. The workshop is partially funded by the Nordunet3 project “COSoDIS” (Contract-Oriented Software Development for Internet Services) and it attracted 25 participants. The program consists of 4 regular papers and 10 invited participant presentations
Considerations in Assuring Safety of Increasingly Autonomous Systems
Recent technological advances have accelerated the development and application of increasingly autonomous (IA) systems in civil and military aviation. IA systems can provide automation of complex mission tasks-ranging across reduced crew operations, air-traffic management, and unmanned, autonomous aircraft-with most applications calling for collaboration and teaming among humans and IA agents. IA systems are expected to provide benefits in terms of safety, reliability, efficiency, affordability, and previously unattainable mission capability. There is also a potential for improving safety by removal of human errors. There are, however, several challenges in the safety assurance of these systems due to the highly adaptive and non-deterministic behavior of these systems, and vulnerabilities due to potential divergence of airplane state awareness between the IA system and humans. These systems must deal with external sensors and actuators, and they must respond in time commensurate with the activities of the system in its environment. One of the main challenges is that safety assurance, currently relying upon authority transfer from an autonomous function to a human to mitigate safety concerns, will need to address their mitigation by automation in a collaborative dynamic context. These challenges have a fundamental, multidimensional impact on the safety assurance methods, system architecture, and V&V capabilities to be employed. The goal of this report is to identify relevant issues to be addressed in these areas, the potential gaps in the current safety assurance techniques, and critical questions that would need to be answered to assure safety of IA systems. We focus on a scenario of reduced crew operation when an IA system is employed which reduces, changes or eliminates a human's role in transition from two-pilot operations
Proceedings of the Deduktionstreffen 2019
The annual meeting Deduktionstreffen is the prime activity of the Special Interest Group on Deduction Systems (FG DedSys) of the AI Section of the German Society for Informatics (GI-FBKI). It is a meeting with a familiar, friendly atmosphere, where everyone interested in deduction can report on their work in an informal setting
Ontology based contextualization and context constraints management in web service processes
The flexibility and dynamism of service-based applications impose shifting the validation process to runtime; therefore, runtime monitoring of dynamic features attached to service-based systems is becoming an important direction
of research that motivated the definition of our work. We propose an ontology based contextualization and a framework and techniques for managing context constraints in a Web service process for dynamic requirements validation
monitoring at process runtime. Firstly, we propose an approach to define and model dynamic service context attached to composition and execution of services
in a service process at run-time. Secondly, managing context constraints are defined in a framework, which has three main processes for context manipulation and reasoning, context constraints generation, and dynamic instrumentation and validation monitoring of context constraints. The dynamic requirements attached to service composition and execution are generated as context constraints.
The dynamic service context modeling is investigated based on empirical analysis of application scenarios in the classical business domain and analysing previous
models in the literature. The orientation of context aspects in a general context taxonomy is considered important. The Ontology Web Language (OWL) has many
merits on formalising dynamic service context such as shared conceptualization, logical language support for composition and reasoning, XML based interoperability,
etc. XML-based constraint representation is compatible with Web service technologies. The analysis of complementary case study scenarios and expert opinions through a survey illustrate the validity and completeness of our context
model. The proposed techniques for context manipulation, context constraints generation, instrumentation and validation monitoring are investigated through a set of experiments from an empirical evaluation. The analytical evaluation is also used to evaluate algorithms. Our contributions and evaluation results provide a further step towards developing a highly automated dynamic requirements
management system for service processes at process run-time
Simulation and statistical model-checking of logic-based multi-agent system models
This thesis presents SALMA (Simulation and Analysis of Logic-Based Multi-
Agent Models), a new approach for simulation and statistical model checking
of multi-agent system models.
Statistical model checking is a relatively new branch of model-based approximative
verification methods that help to overcome the well-known scalability
problems of exact model checking. In contrast to existing solutions,
SALMA specifies the mechanisms of the simulated system by means of logical
axioms based upon the well-established situation calculus. Leveraging
the resulting first-order logic structure of the system model, the simulation
is coupled with a statistical model-checker that uses a first-order variant of
time-bounded linear temporal logic (LTL) for describing properties. This is
combined with a procedural and process-based language for describing agent
behavior. Together, these parts create a very expressive framework for modeling
and verification that allows direct fine-grained reasoning about the agents’
interaction with each other and with their (physical) environment.
SALMA extends the classical situation calculus and linear temporal logic
(LTL) with means to address the specific requirements of multi-agent simulation
models. In particular, cyber-physical domains are considered where
the agents interact with their physical environment. Among other things,
the thesis describes a generic situation calculus axiomatization that encompasses
sensing and information transfer in multi agent systems, for instance
sensor measurements or inter-agent messages. The proposed model explicitly
accounts for real-time constraints and stochastic effects that are inevitable in
cyber-physical systems.
In order to make SALMA’s statistical model checking facilities usable also
for more complex problems, a mechanism for the efficient on-the-fly evaluation
of first-order LTL properties was developed. In particular, the presented algorithm
uses an interval-based representation of the formula evaluation state
together with several other optimization techniques to avoid unnecessary computation.
Altogether, the goal of this thesis was to create an approach for simulation
and statistical model checking of multi-agent systems that builds upon
well-proven logical and statistical foundations, but at the same time takes a
pragmatic software engineering perspective that considers factors like usability,
scalability, and extensibility. In fact, experience gained during several small
to mid-sized experiments that are presented in this thesis suggest that the
SALMA approach seems to be able to live up to these expectations.In dieser Dissertation wird SALMA (Simulation and Analysis of Logic-Based
Multi-Agent Models) vorgestellt, ein im Rahmen dieser Arbeit entwickelter
Ansatz für die Simulation und die statistische Modellprüfung (Model Checking)
von Multiagentensystemen.
Der Begriff „Statistisches Model Checking” beschreibt modellbasierte approximative
Verifikationsmethoden, die insbesondere dazu eingesetzt werden
können, um den unvermeidlichen Skalierbarkeitsproblemen von exakten Methoden
zu entgehen. Im Gegensatz zu bisherigen Ansätzen werden in SALMA die
Mechanismen des simulierten Systems mithilfe logischer Axiome beschrieben,
die auf dem etablierten Situationskalkül aufbauen. Die dadurch entstehende
prädikatenlogische Struktur des Systemmodells wird ausgenutzt um ein Model
Checking Modul zu integrieren, das seinerseits eine prädikatenlogische Variante
der linearen temporalen Logik (LTL) verwendet. In Kombination mit
einer prozeduralen und prozessorientierten Sprache für die Beschreibung von
Agentenverhalten entsteht eine ausdrucksstarke und flexible Plattform für die
Modellierung und Verifikation von Multiagentensystemen. Sie ermöglicht eine
direkte und feingranulare Beschreibung der Interaktionen sowohl zwischen
Agenten als auch von Agenten mit ihrer (physischen) Umgebung.
SALMA erweitert den klassischen Situationskalkül und die lineare temporale
Logik (LTL) um Elemente und Konzepte, die auf die spezifischen Anforderungen
bei der Simulation und Modellierung von Multiagentensystemen
ausgelegt sind. Insbesondere werden cyber-physische Systeme (CPS) unterstützt,
in denen Agenten mit ihrer physischen Umgebung interagieren. Unter
anderem wird eine generische, auf dem Situationskalkül basierende, Axiomatisierung
von Prozessen beschrieben, in denen Informationen innerhalb von
Multiagentensystemen transferiert werden – beispielsweise in Form von Sensor-
Messwerten oder Netzwerkpaketen. Dabei werden ausdrücklich die unvermeidbaren
stochastischen Effekte und Echtzeitanforderungen in cyber-physischen
Systemen berücksichtigt.
Um statistisches Model Checking mit SALMA auch für komplexere Problemstellungen
zu ermöglichen, wurde ein Mechanismus für die effiziente Auswertung
von prädikatenlogischen LTL-Formeln entwickelt. Insbesondere beinhaltet
der vorgestellte Algorithmus eine Intervall-basierte Repräsentation des
Auswertungszustands, sowie einige andere Optimierungsansätze zur Vermeidung
von unnötigen Berechnungsschritten.
Insgesamt war es das Ziel dieser Dissertation, eine Lösung für Simulation
und statistisches Model Checking zu schaffen, die einerseits auf fundierten
logischen und statistischen Grundlagen aufbaut, auf der anderen Seite jedoch
auch pragmatischen Gesichtspunkten wie Benutzbarkeit oder Erweiterbarkeit
genügt. Tatsächlich legen erste Ergebnisse und Erfahrungen aus
mehreren kleinen bis mittelgroßen Experimenten nahe, dass SALMA diesen
Zielen gerecht wird
Dynamic agent safety logic : theory and applications
Modal logic is a family of logics for reasoning about relational structures, broadly construed. It sits at the nexus of philosophy, mathematics, software engineering, and economics. By modeling a target domain as a relational structure, one can define a modal logic for reasoning about its properties. Common examples include modal logics for knowledge, belief, time, program execution, mathematical provability, and ethics. This thesis presents a modal logic that combines several modalities in order to reason about realistic human-like agents. We combine knowledge, belief, action, and safe action, which we call Dynamic Agent Safety Logic, or DASL. We distinguish DASL from other modal logics treating similar topics by arguing that the standard models of human agency are not adequate. We present some criteria a logic of agency should strive to achieve, and then compare how related logics fare. We use the Coq interactive theorem prover to mechanically prove soundness and completeness results for the logic, as well as apply it to case studies in the domain of aviation safety, demonstrating its ability to model realistic, minimally rational agents. Finally, we examine the consequences of modeling agents capable of a certain sort of self-reflection. Such agents face a formal difficulty due to Lob's Theorem, called Lob's Obstacle in the literature. We show how DASL can be relaxed to avoid Lob's Obstacle, while the other modal logics of agency cannot easily do so.Includes bibliographical reference
Design Time Methodology for the Formal Modeling and Verification of Smart Environments
Smart Environments (SmE) are intelligent and complex due to smart connectivity and interaction of heterogeneous devices achieved by complicated and sophisticated computing algorithms. Based on their domotic and industrial applications, SmE system may be critical in terms of correctness, reliability, safety, security and other such vital factors. To achieve error-free and requirement-compliant implementation of these systems, it is advisable to enforce a design process that may guarantee these factors by adopting formal models and formal verification techniques at design time.
The e-Lite research group at Politecnico di Torino is developing solutions for SmE based on integration of commercially available home automation technologies with an intelligent ecosystem based on a central OSGi-based gateway, and distributed collaboration of intelligent applications, with the help of semantic web technologies and applications.
The main goal of my research is to study new methodologies which are used for the modeling and verification of SmE. This goal includes the development of a formal methodology which ensures the reliable implementation of the requirements on SmE, by modeling and verifying each component (users, devices, control algorithms and environment/context) and the interaction among them, especially at various stages in design time, so that all the complexities and ambiguities can be reduced
A model-driven approach to the conceptual modeling of situations : from specification to validation
A modelagem de situações para aplicações sensíveis ao contexto, também
chamadas de aplicações sensíveis a situações, é, por um lado, uma tarefa chave
para o funcionamento adequado dessas aplicações. Por outro lado, essa também é
uma tafera árdua graças à complexidade e à vasta gama de tipos de situações
possíveis. Com o intuito de facilitar a representação desses tipos de situações em
tempo de projeto, foi criada a Linguagem de Modelagem de Situações (Situation
Modeling Language - SML), a qual se baseia parcialmente em ricas teorias
ontológicas de modelagem conceitual, além de fornecer uma plataforma de detecção
de situação em tempo de execução. Apesar do benefício da existência dessa
infraestrutura, a tarefa de definir tipos de situação é ainda não-trivial, podendo
carregar problemas que dificilmente são detectados por modeladores via inspeções
manuais. Esta dissertação tem o propósito de melhorar e facilitar ainda mais a
definição de tipos de situação em SML propondo: (i) uma maior integração da
linguagem com as teorias ontológicas de modelagem conceitual pelo uso da
linguagem OntoUML, visando aumentar a expressividade dos modelos de situação;
e (ii) uma abordagem para validação de tipos de situação usando um método formal,
visando garantir que os modelos criados correspondam à intenção do modelador.
Tanto a integração quanto a validação são implementadas em uma ferramenta para
especificação, verificação e validação de tipos de situação ontologicamente
enriquecidos.The modeling of situation types for context-aware applications, also called situationaware
applications, is, on the one hand, a key task to the proper functioning of those
applications. On the other hand, it is also a hard task given the complexity and the
wide range of possible situation types. Aiming at facilitating the representation of
those types of situations at design-time, the Situation Modeling Language (SML) was
created. This language is based partially on rich ontological theories of conceptual
modeling and is accompanied by a platform for situation-detection at runtime.
Despite the benefits of the availability of this suitable infrastructure, the definition of
situation types, being a non-trivial task, can still pose problems that are hardly
detected by modelers by manual model inspection. This thesis aims at improving and
facilitating the definition of situation types in SML by proposing: (i) the integration
between the language and the ontological theories of conceptual modeling by using
the OntoUML language, with the purpose of increasing the expressivity of situation
type models; and (ii) an approach for the validation of situation type models using a
lightweight formal method, aiming at increasing the correspondence between the
created models’ instances and the modeler’s intentions. Both the integration and the
validation are implemented in a tool for specification, verification and validation of
ontologically-enriched situation types.CAPE
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