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Tom Janßen

Publications and source records attributed to Tom Janßen.

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Approximating $δ$-Dispersion

We consider a continuous facility location problem called $δ$-Dispersion. For some fixed $δ> 0$, the goal is to place as many facilities on a graph as possible with pairwise distance at least $δ$. The facilities may be located on the vertices of the graph, or the interior of the edges. This problem can be interpreted as a continuous version of the well-known Independent Set problem. Its approximation behavior is very similar for large values of $δ$. Notably, Grigoriev et al. [Algorithmica 21] showed that $δ$-Dispersion is solvable in polynomial time when $δ= 1/x$ or $δ= 2/x$ for a natural number $x$ and NP-hard otherwise. We study the approximability of $δ$-Dispersion depending on the value of $δ$. For $δ> 2$, we show poly-APX-hardness, while for all $δ< 2$ that are not solvable in polynomial time we show APX-hardness. Thanks to a translation theorem for $δ$ due to Hartmann et al. [MFCS 22], we may focus our attention for approximation algorithms on the intervals $(2/3 , 1)$ and $(1, 2)$. We provide several approximation algorithms with an approximation factor approaching $1$ as $δ$ approaches one of the interval boundaries. Surprisingly, the behavior as $δ$ approaches $2/3$ from above is different: As our hardness reductions reveal, it is impossible (under standard complexity-theoretic assumptions) to construct an approximation algorithm with an approximation factor approaching $1$ as $δ$ approaches $2/3$ from above.

cs.DS

Continuous Defensive Domination Problems

The problem Defensive $δ$-Covering, for some covering range $δ> 0$, is a continuous facility location problem on undirected graphs where all edges have unit length. It is a generalization of Defensive Dominating Set and $δ$-Covering. An attack and defense are sets of points, which are on vertices or on the interior of an edge. A defense counters an attack, if there is a matching of the points in the defense to the points in the attack, such that any matched points have distance at most $δ$, and every point in the attack is matched. The task is, given a graph $G$ and numbers $\ell, k \in \mathbb N$, to find a defense of size at most $\ell$ that counters every possible attack of size at most $k$. We study the complexity of this problem in various different settings. We show that if the attack is restricted to vertices, the problem is $Σ^P_2$-complete for large $δ$, but if the attack may consist of any points on the graph, it is NP-complete. Additionally, we analyze how the complexity changes if the attacks or defenses may be a multiset. If the defense is allowed to be a multiset, the complexity does not change in any case we consider, while if the attack is allowed to be a multiset, the problem often becomes easier. To show containment in the various complexity classes, we introduce a number of discretization arguments, which show that solutions with a regular structure must always exist.

cs.CC

The Complexity of Graph Exploration Games

Graph Exploration problems ask a searcher to explore an unknown environment. The environment is modeled as a graph, where the searcher needs to visit each vertex beginning at some vertex. Treasure Hunt problems are a variation of Graph Exploration, in which the searcher needs to find a hidden treasure, which is located at a designated vertex. Usually these problems are modeled as online problems, and any online algorithm performs poorly because it has too little knowledge about the instance to react adequately to the requests of the adversary. Thus, the impact of a priori knowledge is of interest. One form of a priori knowledge is an unlabeled map, which is an isomorphic copy of the graph. We analyze Graph Exploration and Treasure Hunt problems with an unlabeled map that is provided to the searcher. For this, we formulate decision variants of both problems by interpreting the online problems as a game between the online algorithm (the searcher) and the adversary. The map, however, is not controllable by the adversary. The question is whether the searcher is able to explore the graph completely or find the treasure for all possible decisions of the adversary. We analyze these games in multiple settings, with and without costs on the edges, on directed and undirected graphs and with different constraints (allowing multiple visits to vertices or edges) on the solution. We prove PSPACE-completeness for most of these games. Additionally, we analyze the complexity of related problems that have additional constraints on the solution.

cs.CC

Approximating $δ$-Covering

$δ$-Covering, for some covering range $δ>0$, is a continuous facility location problem on undirected graphs where all edges have unit length. The facilities may be positioned on the vertices as well as on the interior of the edges. The goal is to position as few facilities as possible such that every point on every edge has distance at most $δ$ to one of these facilities. For large $δ$, the problem is similar to dominating set, which is hard to approximate, while for small $δ$, say close to $1$, the problem is similar to vertex cover. In fact, as shown by Hartmann et al. [Math. Program. 22], $δ$-Covering for all unit-fractions $δ$ is polynomial time solvable, while for all other values of $δ$ the problem is NP-hard. We study the approximability of $δ$-Covering for every covering range $δ>0$. For $δ\geq 3/2$, the problem is log-APX-hard, and allows an $\mathcal O(\log n)$ approximation. For every $δ< 3/2$, there is a constant factor approximation of a minimum $δ$-cover (and the problem is APX-hard when $δ$ is not a unit-fraction). We further study the dependency of the approximation ratio on the covering range $δ< 3/2$. By providing several polynomial time approximation algorithms and lower bounds under the Unique Games Conjecture, we narrow the possible approximation ratio, especially for $δ$ close to the polynomial time solvable cases.

cs.DS

The Complexity of Online Graph Games

Online computation is a concept to model uncertainty where not all information on a problem instance is known in advance. An online algorithm receives requests which reveal the instance piecewise and has to respond with irrevocable decisions. Often, an adversary is assumed that constructs the instance knowing the deterministic behavior of the algorithm. Thus, the adversary is able to tailor the input to any online algorithm. From a game theoretical point of view, the adversary and the online algorithm are players in an asymmetric two-player game. To overcome this asymmetry, the online algorithm is equipped with an isomorphic copy of the graph, which is referred to as unlabeled map. By applying the game theoretical perspective on online graph problems, where the solution is a subset of the vertices, we analyze the complexity of these online vertex subset games. For this, we introduce a framework for reducing online vertex subset games from TQBF. This framework is based on gadget reductions from 3-SATISFIABILITY to the corresponding offline problem. We further identify a set of rules for extending the 3-SATISFIABILITY-reduction and provide schemes for additional gadgets which assure that these rules are fulfilled. By extending the gadget reduction of the vertex subset problem with these additional gadgets, we obtain a reduction for the corresponding online vertex subset game. At last, we provide example reductions for online vertex subset games based on VERTEX COVER, INDEPENDENT SET, and DOMINATING SET, proving that they are PSPACE-complete. Thus, this paper establishes that the online version with a map of NP-complete vertex subset problems form a large class of PSPACE-complete problems.

cs.CC