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: "bad universal priors and notions of optimality"
  Abstract: A big open question of algorithmic information theory is the choice of the universal Turing machine (UTM). For Kolmogorov complexity and Solomonoff induction we have invariance theorems: the choice of the UTM changes bounds only by a constant. For the universally intelligent agent AIXI (Hutter, 2005) no invariance theorem is known. Our results are entirely negative: we discuss cases in which unlucky or adversarial choices of the UTM cause AIXI to misbehave drastically. We show that Legg-Hutter intelligence and thus balanced Pareto optimality is entirely subjective, and that every policy is Pareto optimal in the class of all computable environments. This undermines all existing optimality properties for AIXI. While it may still serve as a gold standard for AI, our results imply that AIXI is a relative theory, dependent on the choice of the UTM.

Connected through hyperedge HE-1 (induced by source paper "intelligence via ultrafilters structural properties of some intelligence comparators of deterministic legg hutter agents"):
  with members:
    - "re evaluating evaluation"
    - "an approximation of the universal intelligence measure"
    - "universal intelligence a definition of machine intelligence"

Connected through hyperedge HE-2 (induced by source paper "universal reinforcement learning algorithms survey and experiments"):
  with members:
    - "count based exploration in feature space for reinforcement learning"
    - "generalised discount functions applied to a monte carlo aimu implementation"
    - "nonparametric general reinforcement learning"
    - "thompson sampling is asymptotically optimal in general environments"
    - "vime variational information maximizing exploration"
    - "unifying count based exploration and intrinsic motivation"
    - "on the computability of solomonoff induction and knowledge seeking"
    - "playing atari with deep reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "thompson sampling is asymptotically optimal in general environments"):
  with members:
    - "a bayesian sampling approach to exploration in reinforcement learning"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"
    - "asymptotically optimal agents"
    - "analysis of thompson sampling for the multi armed bandit problem"
    - "a minimum relative entropy principle for learning and acting"
    - "universal intelligence a definition of machine intelligence"
    - "general discounting versus average reward"
    - "self optimizing and pareto optimal policies in general environments based on bayes mixtures"

Connected through hyperedge HE-4 (induced by source paper "a formal solution to the grain of truth problem"):
  with members:
    - "nonparametric general reinforcement learning"
    - "thompson sampling is asymptotically optimal in general environments"
    - "on the computability of aixi"
    - "on the computability of solomonoff induction and knowledge seeking"
    - "reflective oracles a foundation for classical game theory"
    - "open problems in universal induction intelligence"

Connected through hyperedge HE-5 (induced by source paper "self modification of policy and utility function in rational agents"):
  with members:
    - "thompson sampling is asymptotically optimal in general environments"
    - "avoiding wireheading with value reinforcement learning"
    - "extreme state aggregation beyond mdps"
    - "model based utility functions"
    - "universal intelligence a definition of machine intelligence"

Connected through hyperedge HE-6 (induced by source paper "on the computability of solomonoff induction and knowledge seeking"):
  with members:
    - "on the computability of aixi"
    - "asymptotically optimal agents"
    - "non equivalence of universal priors"
    - "universal prediction of selected bits"
    - "a philosophical treatise of universal induction"
    - "a theory of universal artificial intelligence based on algorithmic complexity"
    - "new error bounds for solomonoff prediction"

Connected through hyperedge HE-7 (induced by source paper "on the computability of aixi"):
  with members:
    - "on the computability of solomonoff induction and knowledge seeking"
    - "non equivalence of universal priors"
    - "a philosophical treatise of universal induction"
    - "a monte carlo aixi approximation"
    - "a theory of universal artificial intelligence based on algorithmic complexity"
    - "new error bounds for solomonoff prediction"

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.AI(Artificial Intelligence)