99,817 research outputs found

    Multiparty Dynamics and Failure Modes for Machine Learning and Artificial Intelligence

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    An important challenge for safety in machine learning and artificial intelligence systems is a~set of related failures involving specification gaming, reward hacking, fragility to distributional shifts, and Goodhart's or Campbell's law. This paper presents additional failure modes for interactions within multi-agent systems that are closely related. These multi-agent failure modes are more complex, more problematic, and less well understood than the single-agent case, and are also already occurring, largely unnoticed. After motivating the discussion with examples from poker-playing artificial intelligence (AI), the paper explains why these failure modes are in some senses unavoidable. Following this, the paper categorizes failure modes, provides definitions, and cites examples for each of the modes: accidental steering, coordination failures, adversarial misalignment, input spoofing and filtering, and goal co-option or direct hacking. The paper then discusses how extant literature on multi-agent AI fails to address these failure modes, and identifies work which may be useful for the mitigation of these failure modes.Comment: 12 Pages, This version re-submitted to Big Data and Cognitive Computing, Special Issue "Artificial Superintelligence: Coordination & Strategy

    Model-based dependability analysis : state-of-the-art, challenges and future outlook

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    Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis

    Practical extensions to the level of repair analysis

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    The level of repair analysis (lora) gives answers to three questions that are posed when deciding on how to maintain capital goods: 1) which components to repair upon failure and which to discard, 2) at which locations in the repair network to perform each type of repairs, and 3) at which locations in the network to deploy resources, such as test equipment. The goal is to achieve the lowest possible life cycle costs. Various models exist for the lora problem. However, these models tend to be restrictive in that specic business situations cannot be incorporated, for example, having repair equipment with a capacity restriction or the occurrence of unsuccessful repairs.We discuss and model various practically relevant extensions to an existing minimum cost \ud ow formulation for the lora problem. We show the added value of these model renements in an extensive numerical experiment

    Enhancing the EAST-ADL error model with HiP-HOPS semantics

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    EAST-ADL is a domain-specific modelling language for the engineering of automotive embedded systems. The language has abstractions that enable engineers to capture a variety of information about design in the course of the lifecycle — from requirements to detailed design of hardware and software architectures. The specification of the EAST-ADL language includes an error model extension which documents language structures that allow potential failures of design elements to be specified locally. The effects of these failures are then later assessed in the context of the architecture design. To provide this type of useful assessment, a language and a specification are not enough; a compiler-like tool that can read and operate on a system specification together with its error model is needed. In this paper we integrate the error model of EAST-ADL with the precise semantics of HiP-HOPS — a state-of-the-art tool that enables dependability analysis and optimization of design models. We present the integration concept between EAST-ADL structure and HiP-HOPS error propagation logic and its transformation into the HiP-HOPS model. Source and destination models are represented using the corresponding XML formats. The connection of these two models at tool level enables practical EAST-ADL designs of embedded automotive systems to be analysed in terms of dependability, i.e. safety, reliability and availability. In addition, the information encoded in the error model can be re-used across different contexts of application with the associated benefits for cost reduction, simplification, and rationalisation of dependability assessments in complex engineering designs

    Structure-Sensitive Mechanism of Nanographene Failure

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    The response of a nanographene sheet to external stresses is considered in terms of a mechanochemical reaction. The quantum chemical realization of the approach is based on a coordinate-of-reaction concept for the purpose of introducing a mechanochemical internal coordinate (MIC) that specifies a deformational mode. The related force of response is calculated as the energy gradient along the MIC, while the atomic configuration is optimized over all of the other coordinates under the MIC constant-pitch elongation. The approach is applied to the benzene molecule and (5, 5) nanographene. A drastic anisotropy in the microscopic behavior of both objects under elongation along a MIC has been observed when the MIC is oriented either along or normally to the C-C bonds chain. Both the anisotropy and high stiffness of the nanographene originate at the response of the benzenoid unit to stress.Comment: 19 pages, 7 figures 1 tabl
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