14.03.2025

Three Papers accepted at AAAI

We are proud that our group members have written three papers for the Annual AAAI Conference on Artificial Intelligence on 27 February - 4 March in Philadelphia, USA. The first titled Strategic Network Creation for Enabling Greedy Routing is based on the master thesis of Julian Berger and co-authored by Tobias Friedrich, Pascal Lenzner, Paraskevi Machaira and Janosch Ruff. The paper introduces the first game-theoretic network creation model with greedy routing, where strategic agents in a metric space aim to create a network that enables all-pairs greedy routing while optimizing connection quality for low-stretch paths.

Second, How Many Lines to Paint the City: Exact Edge-Cover in Temporal Graphs was written by Michelle Döring, George Skretas and Georg Tennigkeit with co-authors from the Royal Holloway University of London. Practically, the authors studied how to assign all connections of a train network to train lines in order to use as few train lines as possible. Mathematically, this corresponds to a covering problem, namely the exact edge-cover by journeys problem. They analyzed the computational complexity of the problem for different restrictions on the train lines and uncovered some variations to be hard to compute, while others allowed for an efficient algorithm.

Finally, we have Efficient Fault-Tolerant Search by Fast Indexing of Sub-Networks written by Sarel Cohen and Tobias Friedrich with co-authors from various universities. The paper is about sensitivity oracles which solve network problems under edge/node failures. The specific problems are L-Hop Shortest Path, k-Path and k-Clique.

Clean Citation Style 005

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Deligkas, Argyrios; Döring, Michelle; Eiben, Eduard; Goldsmith, Tiger-Lily; Skretas, George; Tennigkeit, Georg How Many Lines to Paint the City: Exact Edge-Cover in Temporal GraphsProceedings of the AAAI Conference on Artificial Intelligence 2025: 26498–26506

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Berger, Julian; Friedrich, Tobias; Lenzner, Pascal; Paraskevi, Voula; Ruff, Janosch Strategic Network Creation for Enabling Greedy RoutingConference on Artificial Intelligence (AAAI) 2025

[ Abstract ] [ BibTeX ] [ URL ] [ DOI ] [ Download ]

@article{bflmr-aaai25,
  abstract = {Today we rely on networks that are created and maintained by smart devices. For such networks, there is no governing central authority but instead the network structure is shaped by the decisions of selfish intelligent agents. A key property of such communication networks is that they should be easy to navigate for routing data. For this, a common approach is greedy routing, where every device simply routes data to a neighbor that is closer to the respective destination. Networks of intelligent agents can be analyzed via a game-theoretic approach and in the last decades many variants of network creation games have been proposed and analyzed. In this paper we present the first game-theoretic network creation model that incorporates greedy routing, i.e., the strategic agents in our model are embedded in some metric space and strive for creating a network among themselves where all-pairs greedy routing is enabled. Besides this, the agents optimize their connection quality within the created network by aiming for greedy routing paths with low stretch. For our model, we analyze the existence of (approximate)-equilibria and the computational hardness in different underlying metric spaces. E.g., we characterize the set of equilibria in 1-2-metrics and tree metrics and show that Nash equilibria always exist. For Euclidean space, the setting which is most relevant in practice, we prove that equilibria are not guaranteed to exist but that the well-known \(\Theta\)-graph construction yields networks having a low stretch that are game-theoretically almost stable. For general metric spaces, we show that approximate equilibria exist where the approximation factor depends on the cost of maintaining any link.},
  author = {Berger, Julian and Friedrich, Tobias and Lenzner, Pascal and Paraskevi, Voula and Ruff, Janosch},
  journal = {Conference on Artificial Intelligence (AAAI)},
  keywords = {paraskevimachaira janoschruff julianberger tobiasfriedrich aaai year2025 pascallenzner},
  title = {Strategic Network Creation for Enabling Greedy Routing},
  year = 2025
}