200,379 research outputs found

    A note on knowledge-based programs and specifications

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    Knowledge-based program are programs with explicit tests for knowledge. They have been used successfully in a number of applications. Sanders has pointed out what seem to be a counterintuitive property of knowledge-based programs. Roughly speaking, they do not satisfy a certain monotonicity property, while standard programs (ones without tests for knowledge) do. It is shown that there are two ways of defining the monotonicity property, which agree for standard programs. Knowledge-based programs satisfy the first, but do not satisfy the second. It is further argued by example that the fact that they do not satisfy the second is actually a feature, not a problem. Moreover, once we allow the more general class of knowledge-based specifications, standard programs do not satisfy the monotonicity property either.Comment: To appear, Distributed Computin

    From Uncertainty Data to Robust Policies for Temporal Logic Planning

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    We consider the problem of synthesizing robust disturbance feedback policies for systems performing complex tasks. We formulate the tasks as linear temporal logic specifications and encode them into an optimization framework via mixed-integer constraints. Both the system dynamics and the specifications are known but affected by uncertainty. The distribution of the uncertainty is unknown, however realizations can be obtained. We introduce a data-driven approach where the constraints are fulfilled for a set of realizations and provide probabilistic generalization guarantees as a function of the number of considered realizations. We use separate chance constraints for the satisfaction of the specification and operational constraints. This allows us to quantify their violation probabilities independently. We compute disturbance feedback policies as solutions of mixed-integer linear or quadratic optimization problems. By using feedback we can exploit information of past realizations and provide feasibility for a wider range of situations compared to static input sequences. We demonstrate the proposed method on two robust motion-planning case studies for autonomous driving

    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

    The place of expert systems in a typology of information systems

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    This article considers definitions and claims of Expert Systems ( ES) and analyzes them in view of traditional Information systems (IS). It is argued that the valid specifications for ES do not differ fran those for IS. Consequently the theoretical study and the practical development of ES should not be a monodiscipline. Integration of ES development in classical mathematics and computer science opens the door to existing knowledge and experience. Aspects of existing ES are reviewed from this interdisciplinary point of view
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