Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future

Supporting Newsrooms with Journalistic Knowledge Graph Platforms: Current State and Future Directions

Increasing competition and loss of revenues force newsrooms to explore new digital solutions. The new solutions employ artificial intelligence and big data techniques such as machine learning and knowledge graphs to manage and support the knowledge work needed in all stages of news production. The result is an emerging type of intelligent information system we have called the Journalistic Knowledge Platform (JKP). In this paper, we analyse for the first time knowledge graph-based JKPs in research and practice. We focus on their current state, challenges, opportunities and future directions. Our analysis is based on 14 platforms reported in research carried out in collaboration with news organisations and industry partners and our experiences with developing knowledge graph-based JKPs along with an industry partner. We found that: (a) the most central contribution of JKPs so far is to automate metadata annotation and monitoring tasks; (b) they also increasingly contribute to improving background information and content analysis, speeding-up newsroom workflows and providing newsworthy insights; (c) future JKPs need better mechanisms to extract information from textual and multimedia news items; (d) JKPs can provide a digitalisation path towards reduced production costs and improved information quality while adapting the current workflows of newsrooms to new forms of journalism and readers’ demands.publishedVersio

Brief Announcement: Let It TEE: Asynchronous Byzantine Atomic Broadcast with n ≥ 2f+1

Asynchronous Byzantine Atomic Broadcast (ABAB) promises simplicity in implementation as well as increased performance and robustness in comparison to partially synchronous approaches. We adapt the recently proposed DAG-Rider approach to achieve ABAB with n ≥ 2f+1 processes, of which f are faulty, with only a constant increase in message size. We leverage a small Trusted Execution Environment (TEE) that provides a unique sequential identifier generator (USIG) to implement Reliable Broadcast with n > f processes and show that the quorum-critical proofs still hold when adapting the quorum size to ⌊ n/2 ⌋ + 1. This first USIG-based ABAB preserves the simplicity of DAG-Rider and serves as starting point for further research on TEE-based ABAB

Let It TEE: Asynchronous Byzantine Atomic Broadcast with n ≥ 2f + 1

Asynchronous Byzantine Atomic Broadcast (ABAB) promises, in comparison to partially synchronous approaches, simplicity in implementation, increased performance, and increased robustness. For partially synchronous approaches, it is well-known that small Trusted Execution Environments (TEE), e.g., MinBFT\u27s unique sequential identifier generator (USIG), are capable of reducing the communication effort while increasing the fault tolerance. For ABAB, the research community assumes that the use of TEEs increases performance and robustness. However, despite the existence of a fault-model compiler, a concrete TEE-based approach is not directly available yet. In this brief announcement, we show that the recently proposed DAG-Rider approach can be transformed to provide ABAB with $n\geq 2f+1$ processes, of which $f$ are faulty. We leverage MinBFT\u27s USIG to implement Reliable Broadcast with $n>f$ processes and show that the quorum-critical proofs of DAG-Rider still hold when adapting the quorum size to $\lfloor \frac{n}{2} \rfloor + 1$

Network Latency and Packet Delay Variation in Cyber-physical Systems

The problem addressed in this paper is the limitation imposed by network elements, especially Ethernet elements, on the real-time performance of time-critical systems. Most current network elements are concerned only with data integrity, connection, and throughput with no mechanism for enforcing temporal semantics. Existing safety-critical applications and other applications in industry require varying degrees of control over system-wide temporal semantics. In addition, there are emerging commercial applications that require or will benefit from tighter enforcement of temporal semantics in network elements than is currently possible. This paper examines these applications and requirements and suggests possible approaches to imposing temporal semantics on networks. Model-based design and simulation is used to evaluate the effects of network limitations on time-critical systems