5,648 research outputs found

    A formal approach to modelling and verification of context-aware systems

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    The evolution of smart devices and software technologies has expanded the domain of computing from workplaces to other areas of our everyday life. This trend has been rapidly advancing towards ubiquitous computing environments, where smart devices play an important role in acting intelligently on behalf of the users. One of the sub fields of the ubiquitous computing is context-aware systems. In context-aware systems research, ontology and agent-based technology have emerged as a new paradigm for conceptualizing, designing, and implementing sophisticated software systems. These systems exhibit complex adaptive behaviors, run in highly decentralized environment and can naturally be implemented as agent-based systems. Usually context-aware systems run on tiny resource-bounded devices including smart phones and sensor nodes and hence face various challenges. The lack of formal frameworks in existing research presents a clear challenge to model and verify such systems. This thesis addresses some of these issues by developing formal logical frameworks for modelling and verifying rule-based context-aware multi-agent systems. Two logical frameworks LOCRS and LDROCS have been developed by extending CTL* with belief and communication modalities, which allow us to describe a set of rule-based context-aware reasoning agents with bound on time, memory and communication. The key idea underlying the logical approach of context-aware systems is to define a formal logic that axiomatizes the set of transition systems, and it is then used to state various qualitative and quantitative properties of the systems. The set of rules which are used to model a desired system is derived from OWL 2 RL ontologies. While LOCRS is based on monotonic reasoning where beliefs of an agent cannot be revised based on some contradictory evidence, the LDROCS logic handles inconsistent context information using non-monotonic reasoning. The modelling and verification of a healthcare case study is illustrated using Protégé IDE and Maude LTL model checker

    A formal approach to modelling and verification of context-aware systems

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    The evolution of smart devices and software technologies has expanded the domain of computing from workplaces to other areas of our everyday life. This trend has been rapidly advancing towards ubiquitous computing environments, where smart devices play an important role in acting intelligently on behalf of the users. One of the sub fields of the ubiquitous computing is context-aware systems. In context-aware systems research, ontology and agent-based technology have emerged as a new paradigm for conceptualizing, designing, and implementing sophisticated software systems. These systems exhibit complex adaptive behaviors, run in highly decentralized environment and can naturally be implemented as agent-based systems. Usually context-aware systems run on tiny resource-bounded devices including smart phones and sensor nodes and hence face various challenges. The lack of formal frameworks in existing research presents a clear challenge to model and verify such systems. This thesis addresses some of these issues by developing formal logical frameworks for modelling and verifying rule-based context-aware multi-agent systems. Two logical frameworks LOCRS and LDROCS have been developed by extending CTL* with belief and communication modalities, which allow us to describe a set of rule-based context-aware reasoning agents with bound on time, memory and communication. The key idea underlying the logical approach of context-aware systems is to define a formal logic that axiomatizes the set of transition systems, and it is then used to state various qualitative and quantitative properties of the systems. The set of rules which are used to model a desired system is derived from OWL 2 RL ontologies. While LOCRS is based on monotonic reasoning where beliefs of an agent cannot be revised based on some contradictory evidence, the LDROCS logic handles inconsistent context information using non-monotonic reasoning. The modelling and verification of a healthcare case study is illustrated using Protégé IDE and Maude LTL model checker

    Formal approaches to modelling and verifying resource-bounded agents-state of the art and future prospects

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    This paper reviews formal approaches to modelling and verifying resource-bounded agents focusing on state of the Art and future prospects

    A Logical Framework for the Representation and Verification of Context-aware Agents

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    © 2014, Springer Science+Business Media New York. We propose a logical framework for modelling and verifying context-aware multi-agent systems. We extend CTL∗ with belief and communication modalities, and the resulting logic 𝓛OCRS allows us to describe a set of rule-based reasoning agents with bound on time, memory and communication. The set of rules which are used to model a desired systems is derived from OWL 2 RL ontologies. We provide an axiomatization of the logic and prove it is sound and complete. We show how Maude rewriting system can be used to encode and verify interesting properties of 𝓛OCRS models using existing model checking techniques

    Proceedings of International Workshop "Global Computing: Programming Environments, Languages, Security and Analysis of Systems"

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    According to the IST/ FET proactive initiative on GLOBAL COMPUTING, the goal is to obtain techniques (models, frameworks, methods, algorithms) for constructing systems that are flexible, dependable, secure, robust and efficient. The dominant concerns are not those of representing and manipulating data efficiently but rather those of handling the co-ordination and interaction, security, reliability, robustness, failure modes, and control of risk of the entities in the system and the overall design, description and performance of the system itself. Completely different paradigms of computer science may have to be developed to tackle these issues effectively. The research should concentrate on systems having the following characteristics: ‱ The systems are composed of autonomous computational entities where activity is not centrally controlled, either because global control is impossible or impractical, or because the entities are created or controlled by different owners. ‱ The computational entities are mobile, due to the movement of the physical platforms or by movement of the entity from one platform to another. ‱ The configuration varies over time. For instance, the system is open to the introduction of new computational entities and likewise their deletion. The behaviour of the entities may vary over time. ‱ The systems operate with incomplete information about the environment. For instance, information becomes rapidly out of date and mobility requires information about the environment to be discovered. The ultimate goal of the research action is to provide a solid scientific foundation for the design of such systems, and to lay the groundwork for achieving effective principles for building and analysing such systems. This workshop covers the aspects related to languages and programming environments as well as analysis of systems and resources involving 9 projects (AGILE , DART, DEGAS , MIKADO, MRG, MYTHS, PEPITO, PROFUNDIS, SECURE) out of the 13 founded under the initiative. After an year from the start of the projects, the goal of the workshop is to fix the state of the art on the topics covered by the two clusters related to programming environments and analysis of systems as well as to devise strategies and new ideas to profitably continue the research effort towards the overall objective of the initiative. We acknowledge the Dipartimento di Informatica and Tlc of the University of Trento, the Comune di Rovereto, the project DEGAS for partially funding the event and the Events and Meetings Office of the University of Trento for the valuable collaboration

    A framework for implementing formally verified resource-bounded smart space systems

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    © 2017, Springer Science+Business Media New York. Context-aware computing is a mobile computing paradigm that helps designing and implementing next generation smart applications, where personalized devices interact with users in smart environments. Development of such applications is inherently complex due to these applications adapt to changing contextual information and they often run on resource-bounded devices. Most of the existing context-aware development frameworks are centralized, adopt client–server architecture, and do not consider resource limitations of context-aware devices. This paper presents a systematic framework to modelling and implementation of resource-bounded multi-agent context-aware systems on Android devices. The proposed framework makes use of semantic technologies for context modelling and reasoning about resource-bounded context-aware agents, Android powered smartphones as development platform, a suitable communication model and declarative rule-based programming as a preferred development language

    Logic-Based Specification Languages for Intelligent Software Agents

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    The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used for AOSE. This paper presents a detailed survey of six logic-based executable agent specification languages that have been chosen for their potential to be integrated in our ARPEGGIO project, an open framework for specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each executable language, the logic foundations are described and an example of use is shown. A comparison of the six languages and a survey of similar approaches complete the paper, together with considerations of the advantages of using logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal "Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe Editor-in-Chie

    Model checking ontology-driven reasoning agents using strategy and abstraction

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    We present a framework for the modelling, specification and verification of ontology-driven multi-agent rule-based systems (MASs). We assume that each agent executes in a separate process and that they communicate via message passing. The proposed approach makes use of abstract specifications to model the behaviour of some of the agents in the system, and exploits information about the reasoning strategy adopted by the agents. Abstract specifications are given as Linear Temporal Logic (LTL) formulas which describe the external behaviour of the agents, allowing their temporal behaviour to be compactly modelled. Both abstraction and strategy have been combined in an automated model checking encoding tool Tovrba for rule-based multi-agent systems which allows the system designer to specify information about agents' interaction, behaviour, and execution strategy at different levels of abstraction. The Tovrba tool generates an encoding of the system for the Maude LTL model checker, allowing properties of the system to be verified

    Resilience, reliability, and coordination in autonomous multi-agent systems

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    Acknowledgements The research reported in this paper was funded and supported by various grants over the years: Robotics and AI in Nuclear (RAIN) Hub (EP/R026084/1); Future AI and Robotics for Space (FAIR-SPACE) Hub (EP/R026092/1); Offshore Robotics for Certification of Assets (ORCA) Hub (EP/R026173/1); the Royal Academy of Engineering under the Chair in Emerging Technologies scheme; Trustworthy Autonomous Systems “Verifiability Node” (EP/V026801); Scrutable Autonomous Systems (EP/J012084/1); Supporting Security Policy with Effective Digital Intervention (EP/P011829/1); The International Technology Alliance in Network and Information Sciences.Peer reviewedPostprin
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