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: "algorithmic information theory a brief non technical guide to the field"
  Abstract: This article is a brief guide to the field of algorithmic information theory (AIT), its underlying philosophy, and the most important concepts. AIT arises by mixing information theory and computation theory to obtain an objective and absolute notion of information in an individual object, and in so doing gives rise to an objective and robust notion of randomness of individual objects. This is in contrast to classical information theory that is based on random variables and communication, and has no bearing on information and randomness of individual objects. After a brief overview, the major subfields, applications, history, and a map of the field are presented.

Connected through hyperedge HE-1 (induced by source paper "a philosophical treatise of universal induction"):
  with members:
    - "a complete theory of everything will be subjective"
    - "a monte carlo aixi approximation"
    - "open problems in universal induction intelligence"
    - "algorithmic complexity bounds on future prediction errors"
    - "universal intelligence a definition of machine intelligence"
    - "similarity of objects and the meaning of words"
    - "adaptive online prediction by following the perturbed leader"
    - "convergence and loss bounds for bayesian sequence prediction"

Connected through hyperedge HE-2 (induced by source paper "algorithmic randomness as foundation of inductive reasoning and artificial intelligence"):
  with members:
    - "a complete theory of everything will be subjective"
    - "open problems in universal induction intelligence"
    - "universal algorithmic intelligence a mathematical top down approach"
    - "universal intelligence a definition of machine intelligence"
    - "a theory of universal artificial intelligence based on algorithmic complexity"

Connected through hyperedge HE-3 (induced by source paper "machine learning when and where the horses went astray"):
  with members:
    - "unveiling the mystery of visual information processing in human brain"
    - "algorithmic information theory"
    - "commonsense knowledge ontology and ordinary language"
    - "in quest of image semantics are we looking for it under the right lamppost"
    - "top down unsupervised image segmentation it sounds like oxymoron but actually it is not"
    - "searching for image information content its discovery extraction and representation"
    - "does a plane imitate a bird does computer vision have to follow biological paradigms"

Connected through hyperedge HE-4 (induced by source paper "open problems in universal induction intelligence"):
  with members:
    - "policy iteration for factored mdps"
    - "feature dynamic bayesian networks"
    - "online planning algorithms for pomdps"
    - "feature markov decision processes"
    - "on the possibility of learning in reactive environments with arbitrary dependence"
    - "a collection of definitions of intelligence"
    - "universal algorithmic intelligence a mathematical top down approach"
    - "tests of machine intelligence"

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.IT(Information Theory)