17,871 research outputs found

    Verification of Agent-Based Artifact Systems

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    Artifact systems are a novel paradigm for specifying and implementing business processes described in terms of interacting modules called artifacts. Artifacts consist of data and lifecycles, accounting respectively for the relational structure of the artifacts' states and their possible evolutions over time. In this paper we put forward artifact-centric multi-agent systems, a novel formalisation of artifact systems in the context of multi-agent systems operating on them. Differently from the usual process-based models of services, the semantics we give explicitly accounts for the data structures on which artifact systems are defined. We study the model checking problem for artifact-centric multi-agent systems against specifications written in a quantified version of temporal-epistemic logic expressing the knowledge of the agents in the exchange. We begin by noting that the problem is undecidable in general. We then identify two noteworthy restrictions, one syntactical and one semantical, that enable us to find bisimilar finite abstractions and therefore reduce the model checking problem to the instance on finite models. Under these assumptions we show that the model checking problem for these systems is EXPSPACE-complete. We then introduce artifact-centric programs, compact and declarative representations of the programs governing both the artifact system and the agents. We show that, while these in principle generate infinite-state systems, under natural conditions their verification problem can be solved on finite abstractions that can be effectively computed from the programs. Finally we exemplify the theoretical results of the paper through a mainstream procurement scenario from the artifact systems literature

    Student-Centered Learning: Functional Requirements for Integrated Systems to Optimize Learning

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    The realities of the 21st-century learner require that schools and educators fundamentally change their practice. "Educators must produce college- and career-ready graduates that reflect the future these students will face. And, they must facilitate learning through means that align with the defining attributes of this generation of learners."Today, we know more than ever about how students learn, acknowledging that the process isn't the same for every student and doesn't remain the same for each individual, depending upon maturation and the content being learned. We know that students want to progress at a pace that allows them to master new concepts and skills, to access a variety of resources, to receive timely feedback on their progress, to demonstrate their knowledge in multiple ways and to get direction, support and feedback from—as well as collaborate with—experts, teachers, tutors and other students.The result is a growing demand for student-centered, transformative digital learning using competency education as an underpinning.iNACOL released this paper to illustrate the technical requirements and functionalities that learning management systems need to shift toward student-centered instructional models. This comprehensive framework will help districts and schools determine what systems to use and integrate as they being their journey toward student-centered learning, as well as how systems integration aligns with their organizational vision, educational goals and strategic plans.Educators can use this report to optimize student learning and promote innovation in their own student-centered learning environments. The report will help school leaders understand the complex technologies needed to optimize personalized learning and how to use data and analytics to improve practices, and can assist technology leaders in re-engineering systems to support the key nuances of student-centered learning

    Data in Business Process Models. A Preliminary Empirical Study

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    Traditional activity-centric process modeling languages treat data as simple black boxes acting as input or output for activities. Many alternate and emerging process modeling paradigms, such as case handling and artifact-centric process modeling, give data a more central role. This is achieved by introducing lifecycles and states for data objects, which is beneficial when modeling data-or knowledge-intensive processes. We assume that traditional activity-centric process modeling languages lack the capabilities to adequately capture the complexity of such processes. To verify this assumption we conducted an online interview among BPM experts. The results not only allow us to identify various profiles of persons modeling business processes, but also the problems that exist in contemporary modeling languages w.r.t. The modeling of business data. Overall, this preliminary empirical study confirms the necessity of data-awareness in process modeling notations in general
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