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Parameterized Complexity of Temporal Agony

Data Structures and Algorithms · Submitted 20 Aug 2026

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim We show that the problem is polynomial-time solvable for $k=2$, NP-hard for $k=3$ and $\ell=1$ but polynomial-time solvable for constant $\alpha$, and NP-hard for $k=4$ and $\ell=1$ even for $\alpha=0$.

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arXiv ID2608.20077 (version 1)
Pith IDIQGSB3T6, Pith's permanent record of this paper and its review
CitationAnton Herrmann, Pascal Kunz, Tom-Lukas Breitkopf, Vincent Froese. "Parameterized Complexity of Temporal Agony." arXiv:2608.20077 (2026). https://pith.science/paper/IQGSB3T6
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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 6,342 input tokens.

What the abstract itself states, as probabilities: claims first 0.06 · states limitation 0.25 · human participants 0.02 · controlled comparison 0.01 · randomized assignment 0.01 · states quantitative result 0.96 · compares with prior results 0.19 · mentions code or data availability 0.02.

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arXiv listing abstract v1. Results and the main claim are underlined; .

Real-world networks are often organized in several layers forming a hierarchy which determines the interaction between the individual components. In order to discover such hierarchies in temporal networks, Tatti [ECML PKDD 2018] introduced the temporal agony problem Seg-Agony. Here, the goal is to assign each vertex a certain rank (from 1 to $k$) such that arcs only point from lower ranks to higher ranks. Backward arcs are penalized depending on the difference between the corresponding ranks. Since arcs may change over time, each vertex is allowed to change its rank $\ell\ge 1$ times in order to minimize the overall penalty $\alpha$ (called temporal agony). We study the parameterized complexity of Seg-Agony with a special focus on the number $k$ of possible ranks for which we identify the precise complexity border. We show that the problem is polynomial-time solvable for $k=2$, NP-hard for $k=3$ and $\ell=1$ but polynomial-time solvable for constant $\alpha$, and NP-hard for $k=4$ and $\ell=1$ even for $\alpha=0$. We further show a polynomial-time algorithm for a constant number $n$ of vertices and fixed-parameter tractability for the combined parameter $n+\ell$.

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#sentencerolethe authors' own workstates the main conclusionstrength
s0 Real-world networks are often organized in several layers forming a hierarchy which determines the interaction between the individual components. background 1.00 0.05 0.01 asserted 0.78
s1 In order to discover such hierarchies in temporal networks, Tatti [ECML PKDD 2018] introduced the temporal agony problem Seg-Agony. background 1.00 0.03 0.03 asserted 1.00
s2 Here, the goal is to assign each vertex a certain rank (from 1 to $k$) such that arcs only point from lower ranks to higher ranks. background 0.84 0.07 0.02 asserted 1.00
s3 Backward arcs are penalized depending on the difference between the corresponding ranks. background 0.81 0.08 0.02 asserted 1.00
s4 Since arcs may change over time, each vertex is allowed to change its rank $\ell\ge 1$ times in order to minimize the overall penalty $\alpha$ (called temporal agony). background 0.84 0.13 0.03 asserted 0.79
s5 We study the parameterized complexity of Seg-Agony with a special focus on the number $k$ of possible ranks for which we identify the precise complexity border. contribution 1.00 0.86 0.10 asserted 0.86
s6 We show that the problem is polynomial-time solvable for $k=2$, NP-hard for $k=3$ and $\ell=1$ but polynomial-time solvable for constant $\alpha$, and NP-hard for $k=4$ and $\ell=1$ even for $\alpha=0$. result 0.99 0.96 0.76 asserted 1.00
s7 We further show a polynomial-time algorithm for a constant number $n$ of vertices and fixed-parameter tractability for the combined parameter $n+\ell$. result 0.91 0.97 0.17 asserted 1.00

What kind of paper the classifier reports this is: theoretical result 1.00 · evidence from proof or derivation 1.00.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Real-world networks are often organized in several layers forming a hierarchy which determines the interaction between the individual components. In order to discover such hierarchies in temporal networks, Tatti [ECML PKDD 2018] introduced the temporal agony problem Seg-Agony. Here, the goal is to assign each vertex a certain rank (from 1 to $k$) such that arcs only point from lower ranks to higher ranks. Backward arcs are penalized depending on the difference between the corresponding ranks. Since arcs may change over time, each vertex is allowed to change its rank $\ell\ge 1$ times in order to minimize the overall penalty $\alpha$ (called temporal agony). We study the parameterized complexity of Seg-Agony with a special focus on the number $k$ of possible ranks for which we identify the precise complexity border. We show that the problem is polynomial-time solvable for $k=2$, NP-hard for $k=3$ and $\ell=1$ but polynomial-time solvable for constant $\alpha$, and NP-hard for $k=4$ and $\ell=1$ even for $\alpha=0$. We further show a polynomial-time algorithm for a constant number $n$ of vertices and fixed-parameter tractability for the combined parameter $n+\ell$.

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