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 "projective simulation with generalization"):
  Abstract: The ability to generalize is an important feature of any intelligent agent. Not only because it may allow the agent to cope with large amounts of data, but also because in some environments, an agent with no generalization capabilities cannot learn. In this work we outline several criteria for generalization, and present a dynamic and autonomous machinery that enables projective simulation agents to meaningfully generalize. Projective simulation, a novel, physical approach to artificial intelligence, was recently shown to perform well in standard reinforcement learning problems, with applications in advanced robotics as well as quantum experiments. Both the basic projective simulation model and the presented generalization machinery are based on very simple principles. This allows us to provide a full analytical analysis of the agent’s performance and to illustrate the benefit the agent gains by generalizing. Specifically, we show that already in basic (but extreme) environments, learning without generalization may be impossible, and demonstrate how the presented generalization machinery enables the projective simulation agent to learn.

Includes members:
  Member "meta learning within projective simulation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the convergence of projective simulation based reinforcement learning in markov decision processes")
  Member "robotic playing for hierarchical complex skill learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "self supervised damage avoiding manipulation strategy optimization via mental simulation")
  Member "projective simulation applied to the grid world and the mountain car problem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "aerial animal biometrics individual friesian cattle recovery and visual identification via an autonomous uav with onboard deep inference")
  Member "feature reinforcement learning in practice":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "extreme state aggregation beyond mdps")
  Member "feature reinforcement learning part i unstructured mdps":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a geometric perspective on optimal representations for reinforcement learning")
  Member "bandit problems with side observations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "bounded regret for finitely parameterized multi armed bandits")

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)