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 "fractal dimension versus process complexity"):
  Abstract: Complexity measures are designed to capture complex behavior and quantify *how* complex, according to that measure, that particular behavior is. It can be expected that different complexity measures from possibly entirely different fields are related to each other in a non-trivial fashion. Here we study small Turing machines (TMs) with two symbols, and two and three states. For any particular such machine $\tau$ and any particular input $x$ we consider what we call the 'space-time' diagram which is the collection of consecutive tape configurations of the computation $\tau(x)$. In our setting, we define fractal dimension of a Turing machine as the limiting fractal dimension of the corresponding space-time diagram. It turns out that there is a very strong relation between the fractal dimension of a Turing machine of the above-specified type and its runtime complexity. In particular, a TM with three states and two colors runs in at most linear time iff its dimension is 2, and its dimension is 1 iff it runs in super-polynomial time and it uses polynomial space. If a TM runs in time $O(x^n)$ we have empirically verified that the corresponding dimension is $(n+1)/n$, a result that we can only partially prove. We find the results presented here remarkable because they relate two completely different complexity measures: the geometrical fractal dimension on the one side versus the time complexity of a computation on the other side.

Includes members:
  Member "complexity fits the fittest":
    also connected through other hyperedges:
      (none)
  Member "on the necessity of complexity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ab initio algorithmic causal deconvolution of intertwined programs and networks by generative mechanism")
  Member "on the dynamic qualitative behaviour of universal computation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "asymptotic intrinsic universality and natural reprogrammability by behavioural emulation")
  Member "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ab initio algorithmic causal deconvolution of intertwined programs and networks by generative mechanism")
  Member "empirical encounters with computational irreducibility and unpredictability":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "quantifying natural and artificial intelligence in robots and natural systems with an algorithmic behavioural test")
  Member "compression based investigation of the dynamical properties of cellular automata and other systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the information theoretic and algorithmic approach to human animal and artificial cognition")
  Member "the dimensions of individual strings and sequences":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "who asked us how the theory of computing answers questions about analysis")

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.CC(Computational Complexity)