TY - GEN A1 - Böhne, Sebastian A1 - Kreitz, Christoph T1 - Learning how to prove BT - from the coq proof assistant to textbook style T2 - Electronic proceedings in theoretical computer science N2 - We have developed an alternative approach to teaching computer science students how to prove. First, students are taught how to prove theorems with the Coq proof assistant. In a second, more difficult, step students will transfer their acquired skills to the area of textbook proofs. In this article we present a realisation of the second step. Proofs in Coq have a high degree of formality while textbook proofs have only a medium one. Therefore our key idea is to reduce the degree of formality from the level of Coq to textbook proofs in several small steps. For that purpose we introduce three proof styles between Coq and textbook proofs, called line by line comments, weakened line by line comments, and structure faithful proofs. While this article is mostly conceptional we also report on experiences with putting our approach into practise. Y1 - 2018 U6 - https://doi.org/10.4204/EPTCS.267.1 SN - 2075-2180 IS - 267 SP - 1 EP - 18 PB - Open Publishing Association CY - Sydney ER - TY - GEN A1 - Brewka, Gerhard A1 - Schaub, Torsten H. A1 - Woltran, Stefan T1 - Interview with Gerhard Brewka T2 - Künstliche Intelligenz N2 - This interview with Gerhard Brewka was conducted by correspondance in May 2018. The question set was compiled by Torsten Schaub and Stefan Woltran. Y1 - 2018 U6 - https://doi.org/10.1007/s13218-018-0549-5 SN - 0933-1875 SN - 1610-1987 VL - 32 IS - 2-3 SP - 219 EP - 221 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Bosser, Anne-Gwenn A1 - Cabalar, Pedro A1 - Dieguez, Martin A1 - Schaub, Torsten H. T1 - Introducing temporal stable models for linear dynamic logic T2 - 16th International Conference on Principles of Knowledge Representation and Reasoning N2 - We propose a new temporal extension of the logic of Here-and-There (HT) and its equilibria obtained by combining it with dynamic logic over (linear) traces. Unlike previous temporal extensions of HT based on linear temporal logic, the dynamic logic features allow us to reason about the composition of actions. For instance, this can be used to exercise fine grained control when planning in robotics, as exemplified by GOLOG. In this paper, we lay the foundations of our approach, and refer to it as Linear Dynamic Equilibrium Logic, or simply DEL. We start by developing the formal framework of DEL and provide relevant characteristic results. Among them, we elaborate upon the relationships to traditional linear dynamic logic and previous temporal extensions of HT. Y1 - 2018 UR - https://www.dc.fi.udc.es/~cabalar/del.pdf SP - 12 EP - 21 PB - ASSOC Association for the Advancement of Artificial Intelligence CY - Palo Alto ER - TY - GEN A1 - Bordihn, Henning A1 - Nagy, Benedek A1 - Vaszil, György T1 - Preface: Non-classical models of automata and applications VIII T2 - RAIRO-Theoretical informatics and appli and applications Y1 - 2018 U6 - https://doi.org/10.1051/ita/2018019 SN - 0988-3754 SN - 1290-385X VL - 52 IS - 2-4 SP - 87 EP - 88 PB - EDP Sciences CY - Les Ulis ER - TY - GEN A1 - Alhosseini Almodarresi Yasin, Seyed Ali A1 - Bin Tareaf, Raad A1 - Najafi, Pejman A1 - Meinel, Christoph T1 - Detect me if you can BT - Spam Bot Detection Using Inductive Representation Learning T2 - Companion Proceedings of The 2019 World Wide Web Conference N2 - Spam Bots have become a threat to online social networks with their malicious behavior, posting misinformation messages and influencing online platforms to fulfill their motives. As spam bots have become more advanced over time, creating algorithms to identify bots remains an open challenge. Learning low-dimensional embeddings for nodes in graph structured data has proven to be useful in various domains. In this paper, we propose a model based on graph convolutional neural networks (GCNN) for spam bot detection. Our hypothesis is that to better detect spam bots, in addition to defining a features set, the social graph must also be taken into consideration. GCNNs are able to leverage both the features of a node and aggregate the features of a node’s neighborhood. We compare our approach, with two methods that work solely on a features set and on the structure of the graph. To our knowledge, this work is the first attempt of using graph convolutional neural networks in spam bot detection. KW - Social Media Analysis KW - Bot Detection KW - Graph Embedding KW - Graph Convolutional Neural Networks Y1 - 2019 SN - 978-1-4503-6675-5 U6 - https://doi.org/10.1145/3308560.3316504 SP - 148 EP - 153 PB - Association for Computing Machinery CY - New York ER - TY - GEN ED - Plattner, Hasso ED - Meinel, Christoph ED - Leifer, Larry T1 - Design thinking : understand - improve - apply Y1 - 2011 SN - 978-3-642-13756-3 PB - Springer-Verlag Berlin Heidelberg CY - Berlin, Heidelberg ER -