Congestion Games with Mixed Objectives - Feldotto, Matthias; Leder, Lennart; Skopalik, Alexander (Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA))
We study a new class of games which generalizes congestion games and its bottleneck variant. We introduce congestion games with mixed objectives to model network scenarios in which players seek to optimize for latency and bandwidths alike. We characterize the existence of pure Nash equilibria (PNE) and the convergence of improvement dynamics. For games that do not possess PNE we give bounds on the approximation ratio of approximate pure Nash equilibria.

Money Talks (Even) in the Sharing Economy: Empirical Evidence for Price Effects in Online Ratings as Quality Signals - Gutt, Dominik; Kundisch, Dennis (Proceedings of the 37th International Conference on Information Systems (ICIS), Dublin, Ireland)
Recent literature reports concerns about implausibly high Overall ratings in the sharing economy, which undermines the credibility of this rating as a quality signal. This study empirically investigates the relationship between quality and price, commonly captured by the Value dimension in multidimensional rating systems, to reveal whether reviewers form a perception of quality that they then express in the Value dimension, rather than in the Overall rating. We test our hypotheses on a comprehensive panel dataset for 14,859 Airbnb listings in New York. Our preliminary empirical findings show that an increase in price leads to a significant and substantial decrease in the Value rating, suggesting that Value ratings can offer a valuable source of information for potential buyers in addition to the supposedly inflated Overall rating. Moreover, this mechanism has substantial implications for potential buyers who seek to evaluate a listing’s quality and for a seller’s price setting.

Kommunikationskulturen in digitalen Welten. Konzepte und Strategien der Medienpädagogik und Medienbildung - Brüggemann, M.; Knaus, T.; Meister, Dorothee M.

Mediengestütztes Lernen in der Pflege - zwischen Traditionen und Innovationen - Kamin, A. M.; Greiner, A.-D.; Meister, Dorothee M.; Darmann-Finck, I.

Nibbler: Implementing a Turing machine to simulate the Busy Beaver problem - Heuchler, Sebastian

Kommunikationskulturen in digitalen Welten. Konzepte und Strategien der Medienpädagogik und Medienbildung. (Vorwort) - Brüggemann, M.; Knaus, T.; Meister, Dorothee M. (Kommunikationskulturen in digitalen Welten. Konzepte und Strategien der Medienpädagogik und Medienbildung)

Qualifizierung von Erzieherinnen und Erziehern zur frühkindlichen Medienbildung in Kindertagesstätten - Friedrichs-Liesenkötter, H.; Meister, Dorothee M. (Krippe, Kita, Kinderzimmer – Medienpädagogik von Anfang an – Medienpädagogische Konzepte und Perspektiven)

Increasing Educational Opportunities through Digital Participation - Kamin, A.-M.; Meister, Dorothee M. (Universal Access in Human-Computer Interaction: Methods, Techniques, and Best Practices. 10th International Conference, UAHCI 2016 Held as Part of HCI International 2016 Toronto, Canada, Juli 17- 22, 2016, Proceedings, Part III)

MeCoPflege im Detail – Qualifizierung. Lernplattform. Medienpoints - Kamin, A.-M.; Greiner, A.-D.; Darmann-Finck, I.; Meister, Dorothee M. (Mediengestütztes Lernen in der Pflege – zwischen Traditionen und Innovationen)

Mediengestütztes Lernen in der Pflege - zwischen Traditionen und Innovationen. Einführende Gedanken - Kamin, A.-M.; Greiner, A.-D.; Meister, Dorothee M.; Darmann-Finck, I. (Mediengestütztes Lernen in der Pflege - zwischen Traditionen und Innovationen)

Digital unterstütztes Lernen in der beruflichen Bildung - Potenziale und Bedarfe bei den Pflege und Gesundheitsberufen - Kamin, A.-M.; Meister, Dorothee M. (Mediengestütztes Lernen in der Pflege - zwischen Traditionen und Innovationen)

Usability-Aspekte von virtuellen Lernplattformen am Beispiel von MeCoPdlege - Beckmann, A.; Meister, Dorothee M. (Mediengestütztes Lernen in der Pflege - zwischen Traditionen und Innovationen)

Modellierung von domänenspezifischen Ontologien im Anwendungsfall funktionaler Softwareanforderungen - Stanco, Stefan

Marktmissbrauch in der Internetökonomie - Eine wettbewerbspolitische Analyse - Kesmen, Belma

Literaturüberblick zur Varianz in Kundenbewertungen auf Online Plattformen - Jubrail, Ari

SplayNet: Towards Locally Self-Adjusting Networks - Schmid, Stefan; Avin, Chen; Scheideler, Christian; Borokhovich, Michael; Haeupler, Bernhard; Lotker, Zvi (IEEE/ACM Trans. Netw.)

On the Runtime of Universal Coating for Programmable Matter - Derakhshandeh, Zahra; Gmyr, Robert; Porter, Alexandra; W. Richa, Andrea; Scheideler, Christian; Strothmann, Thim Frederik (DNA Computing and Molecular Programming - 22nd International Conference, DNA 22, Munich, Germany, September 4-8, 2016, Proceedings)

Universal Shape Formation for Programmable Matter - Derakhshandeh, Zahra; Gmyr, Robert; W. Richa, Andrea; Scheideler, Christian; Strothmann, Thim Frederik (Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2016, Asilomar State Beach/Pacific Grove, CA, USA, July 11-13, 2016)

Learning to Aggregate Using Uninorms - Melnikov, Vitaly; Hüllermeier, Eyke (Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016))
In this paper, we propose a framework for a class of learning problems that we refer to as “learning to aggregate”. Roughly, learning-to-aggregate problems are supervised machine learning problems, in which instances are represented in the form of a composition of a (variable) number on constituents; such compositions are associated with an evaluation, score, or label, which is the target of the prediction task, and which can presumably be modeled in the form of a suitable aggregation of the properties of its constituents. Our learning-to-aggregate framework establishes a close connection between machine learning and a branch of mathematics devoted to the systematic study of aggregation functions. We specifically focus on a class of functions called uninorms, which combine conjunctive and disjunctive modes of aggregation. Experimental results for a corresponding model are presented for a review data set, for which the aggregation problem consists of combining different reviewer opinions about a paper into an overall decision of acceptance or rejection.

Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2016, Asilomar State Beach/Pacific Grove, CA, USA, July 11-13, 2016