The temporal explorer who returns to the base
Eleni C. Akrida, George B. Mertzios, Paul G. Spirakis

TL;DR
This paper investigates the computational complexity of exploring temporal star graphs, identifying tractable cases and establishing NP-completeness and APX-hardness for larger k, along with approximation algorithms.
Contribution
It provides a systematic complexity analysis of temporal star exploration, including efficient algorithms for small k and hardness results for larger k, plus approximation methods.
Findings
Efficient algorithms for StarExp(3) and MaxStarExp(2).
NP-completeness of StarExp(k) for k >= 6.
APX-hardness and a 2-approximation algorithm for MaxStarExp(k).
Abstract
In this paper we study the problem of exploring a temporal graph (i.e. a graph that changes over time), in the fundamental case where the underlying static graph is a star. The aim of the exploration problem in a temporal star is to find a temporal walk which starts at the center of the star, visits all leafs, and eventually returns back to the center. We initiate a systematic study of the computational complexity of this problem, depending on the number k of time-labels that every edge is allowed to have; that is, on the number k of time points where every edge can be present in the graph. To do so, we distinguish between the decision version StarExp(k) asking whether a complete exploration of the instance exists, and the maximization version MaxStarExp(k) of the problem, asking for an exploration schedule of the greatest possible number of edges in the star. We present here a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
