human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "energy consumption of group search on a line"):
  Abstract: Consider two robots that start at the origin of the infinite line in search of an exit at an unknown location on the line. The robots can only communicate if they arrive at the same location at exactly the same time, i.e. they use the so-called face-to-face communication model. The group search time is defined as the worst-case time as a function of $d$, the distance of the exit from the origin, when both robots can reach the exit. It has long been known that for a single robot traveling at unit speed, the search time is at least $9d-o(d)$. It was shown recently that $k\geq2$ robots traveling at unit speed also require at least $9d$ group search time. #R##N#We investigate energy-time trade-offs in group search by two robots, where the energy loss experienced by a robot traveling a distance $x$ at constant speed $s$ is given by $s^2 x$. Specifically, we consider the problem of minimizing the total energy used by the robots, under the constraints that the search time is at most a multiple $c$ of the distance $d$ and the speed of the robots is bounded by $b$. Motivation for this study is that for the case when robots must complete the search in $9d$ time with maximum speed one, a single robot requires at least $9d$ energy, while for two robots, all previously proposed algorithms consume at least $28d/3$ energy. #R##N#When the robots have bounded memory, we generalize existing algorithms to obtain a family of optimal (and in some cases nearly optimal) algorithms parametrized by pairs of $b,c$ values that can solve the problem for the entire spectrum of these pairs for which the problem is solvable. We also propose a novel search algorithm, with unbounded memory, that simultaneously achieves search time $9d$ and consumes energy $8.42588d$. Our result shows that two robots can search on the line in optimal time $9d$ while consuming less total energy than a single robot within the same search time.

Includes members:
  Member "average case worst case tradeoffs for evacuating 2 robots from the disk in the face to face model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "probabilistically faulty searching on a half line")
  Member "god save the queen":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "time energy tradeoffs for evacuation by two robots in the wireless model")
  Member "priority evacuation from a disk using mobile robots":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "time energy tradeoffs for evacuation by two robots in the wireless model")
  Member "linear search with terrain dependent speeds":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "probabilistically faulty searching on a half line")
  Member "search on a line by byzantine robots":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "time energy tradeoffs for evacuation by two robots in the wireless model")
  Member "fast two robot disk evacuation with wireless communication":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "probabilistically faulty searching on a half line")
  Member "search and fetch with 2 robots on a disk wireless and face to face communication models":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "probabilistically faulty searching on a half line")
  Member "evacuating robots from a disk using face to face communication":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "time energy tradeoffs for evacuation by two robots in the wireless model")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DM(Discrete Mathematics)