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 "quantifying natural and artificial intelligence in robots and natural systems with an algorithmic behavioural test"):
  Abstract: One of the most important aims of the fields of robotics, artificial intelligence and artificial life is the design and construction of systems and machines as versatile and as reliable as living organisms at performing high level human-like tasks. But how are we to evaluate artificial systems if we are not certain how to measure these capacities in living systems, let alone how to define life or intelligence? Here I survey a concrete metric towards measuring abstract properties of natural and artificial systems, such as the ability to react to the environment and to control one's own behaviour.

Includes members:
  Member "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the thermodynamics of network coding and an algorithmic refinement of the principle of maximum entropy")
  Member "what is nature like computation a behavioural approach and a notion of programmability":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "paths to unconventional computing causality in complexity")
  Member "calculating kolmogorov complexity from the output frequency distributions of small turing machines":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how incomputable is kolmogorov complexity")
  Member "on the dynamic qualitative behaviour of universal computation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (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-6 (induced by source paper "what is nature like computation a behavioural approach and a notion of programmability")

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.AI(Artificial Intelligence)