human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "passively mobile communicating machines that use restricted space"
  Abstract: We propose a new theoretical model for passively mobile Wireless Sensor Networks, called PM, standing for Passively mobile Machines. The main modification w.r.t. the Population Protocol model is that agents now, instead of being automata, are Turing Machines. We provide general definitions for unbounded memories, but we are mainly interested in computations upper-bounded by plausible space limitations. However, we prove that our results hold for more general cases. We focus on complete communication graphs and define the complexity classes PMSPACE(f(n)) parametrically, consisting of all predicates that are stably computable by some PM protocol that uses O(f(n)) memory on each agent. We provide a protocol that generates unique ids from scratch only by using O(log n) memory, and use it to provide an exact characterization for the classes PMSPACE(f(n)) when f(n)={\Omega}(log n): they are precisely the classes of all symmetric predicates in NSPACE(nf(n)). In this way, we provide a space hierarchy for the PM model when the memory bounds are {\Omega}(log n). Finally, we explore the computability of the PM model when the protocols use o(loglog n) space per machine and prove that SEMILINEAR=PMSPACE(f(n)) when f(n)=o(loglog n), where SEMILINEAR denotes the class of the semilinear predicates. In fact, we prove that this bound acts as a threshold, so that SEMILINEAR is a proper subset of PMSPACE(f(n)) when f(n)=O(loglog n).

Connected through hyperedge HE-1 (induced by source paper "robust comparison in population protocols"):
  with members:
    - "majority stabilization in population protocols"
    - "fast space optimal leader election in population protocols"
    - "robust detection in leak prone population protocols"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "determining majority in networks with local interactions and very small local memory"
    - "the computational power of population protocols"

Connected through hyperedge HE-2 (induced by source paper "almost logarithmic time space optimal leader election in population protocols"):
  with members:
    - "fast space optimal leader election in population protocols"
    - "logarithmic expected time leader election in population protocol model"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "time vs information tradeoffs for leader election in anonymous trees"
    - "on convergence and threshold properties of discrete lotka volterra population protocols"
    - "stable leader election in population protocols requires linear time"
    - "plurality consensus in the gossip model"

Connected through hyperedge HE-3 (induced by source paper "hardness of computing and approximating predicates and functions with leaderless population protocols"):
  with members:
    - "fast space optimal leader election in population protocols"
    - "robustness of expressivity in chemical reaction networks"
    - "democratic existential and consensus based output conventions in stable computation by chemical reaction networks"
    - "how many cooks spoil the soup"
    - "stable leader election in population protocols requires linear time"
    - "leaderless deterministic chemical reaction networks"
    - "timing in chemical reaction networks"
    - "deterministic function computation with chemical reaction networks"

Connected through hyperedge HE-4 (induced by source paper "fast space optimal leader election in population protocols"):
  with members:
    - "space optimal majority in population protocols"
    - "phase clocks for transient fault repair"

Connected through hyperedge HE-5 (induced by source paper "how many cooks spoil the soup"):
  with members:
    - "terminating distributed construction of shapes and patterns in a fair solution of automata"
    - "on convergence and threshold properties of discrete lotka volterra population protocols"
    - "stable leader election in population protocols requires linear time"
    - "netcs a new simulator of population protocols and network constructors"
    - "simple and efficient local codes for distributed stable network construction"
    - "leaderless deterministic chemical reaction networks"
    - "timing in chemical reaction networks"
    - "deterministic function computation with chemical reaction networks"

Connected through hyperedge HE-6 (induced by source paper "time space trade offs in molecular computation"):
  with members:
    - "plurality consensus via shuffling lessons learned from load balancing"
    - "programming discrete distributions with chemical reaction networks"
    - "tight lower bounds for data dependent locality sensitive hashing"
    - "stable leader election in population protocols requires linear time"
    - "determining majority in networks with local interactions and very small local memory"
    - "timing in chemical reaction networks"

Connected through hyperedge HE-7 (induced by source paper "population protocols with faulty interactions the impact of a leader"):
  with members:
    - "on the power of weaker pairwise interaction fault tolerant simulation of population protocols"
    - "time varying graphs and dynamic networks"
    - "on the convergence of population protocols when population goes to infinity"
    - "the dynamics of probabilistic population protocols"

Connected through hyperedge HE-8 (induced by source paper "time space trade offs in population protocols"):
  with members:
    - "programming discrete distributions with chemical reaction networks"
    - "stable leader election in population protocols requires linear time"
    - "timing in chemical reaction networks"

Question: Please tell me which class the center node 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.CC(Computational Complexity)