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: "classification of random boolean networks"
  Abstract: We provide the first classification of different types of Random Boolean Networks (RBNs). We study the differences of RBNs depending on the degree of synchronicity and determinism of their updating scheme. For doing so, we first define three new types of RBNs. We note some similarities and differences between different types of RBNs with the aid of a public software laboratory we developed. Particularly, we find that the point attractors are independent of the updating scheme, and that RBNs are more different depending on their determinism or non-determinism rather than depending on their synchronicity or asynchronicity. We also show a way of mapping non-synchronous deterministic RBNs into synchronous RBNs. Our results are important for justifying the use of specific types of RBNs for modelling natural phenomena.

Connected through hyperedge HE-1 (induced by source paper "discrete and fuzzy dynamical genetic programming in the xcsf learning classifier system"):
  with members:
    - "discrete dynamical genetic programming in xcs"

Connected through hyperedge HE-2 (induced by source paper "on mobile dna in artificial regulatory networks evolving functional and structural dynamism"):
  with members:
    - "gene expression programming a new adaptive algorithm for solving problems"

Connected through hyperedge HE-3 (induced by source paper "complexity and information measuring emergence self organization and homeostasis at multiple scales"):
  with members:
    - "learning social intelligence and the turing test why an out of the box turing machine will not pass the turing test"
    - "the world as evolving information"
    - "numerical evaluation of algorithmic complexity for short strings a glance into the innermost structure of randomness"
    - "computing networks a general framework to contrast neural and swarm cognitions"
    - "image characterization and classification by physical complexity"
    - "compression based investigation of the dynamical properties of cellular automata and other systems"
    - "on the kolmogorov chaitin complexity for short sequences"

Connected through hyperedge HE-4 (induced by source paper "on natural genetic engineering structural dynamism in random boolean networks"):
  with members:
    - "gene expression programming a new adaptive algorithm for solving problems"

Connected through hyperedge HE-5 (induced by source paper "computing networks a general framework to contrast neural and swarm cognitions"):
  with members:
    - "the world as evolving information"
    - "the use of ideas of information theory for studying language and intelligence in ants"

Connected through hyperedge HE-6 (induced by source paper "assessing random dynamical network architectures for nanoelectronics"):
  with members:
    - "nature inspired interconnects for self assembled large scale network on chip designs"

Connected through hyperedge HE-7 (induced by source paper "a comparison of different cognitive paradigms using simple animats in a virtual laboratory with implications to the notion of cognition"):
  with members:
    - "a model for combination of external and internal stimuli in the action selection of an autonomous agent"
    - "behaviour based knowledge systems an epigenetic path from behaviour to knowledge"
    - "adaptive development of koncepts in virtual animats insights into the development of knowledge"
    - "dynamic adjustment of the motivation degree in an action selection mechanism"
    - "thinking adaptive towards a behaviours virtual laboratory"

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)