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 "mapping hearthstone deck spaces through map elites with sliding boundaries"):
  Abstract: Quality diversity (QD) algorithms such as MAP-Elites have emerged as a powerful alternative to traditional single-objective optimization methods. They were initially applied to evolutionary robotics problems such as locomotion and maze navigation, but have yet to see widespread application. We argue that these algorithms are perfectly suited to the rich domain of video games, which contains many relevant problems with a multitude of successful strategies and often also multiple dimensions along which solutions can vary. #R##N#This paper introduces a novel modification of the MAP-Elites algorithm called MAP-Elites with Sliding Boundaries (MESB) and applies it to the design and rebalancing of Hearthstone, a popular collectible card game chosen for its number of multidimensional behavior features relevant to particular styles of play. To avoid overpopulating cells with conflated behaviors, MESB slides the boundaries of cells based on the distribution of evolved individuals. Experiments in this paper demonstrate the performance of MESB in Hearthstone. Results suggest MESB finds diverse ways of playing the game well along the selected behavioral dimensions. Further analysis of the evolved strategies reveals common patterns that recur across behavioral dimensions and explores how MESB can help rebalance the game.

Includes members:
  Member "monte carlo tree search for simulation based strategy analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "conceptual game expansion")
  Member "talakat bullet hell generation through constrained map elites":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mech elites illuminating the mechanic space of gvgai")
  Member "q deckrec a fast deck recommendation system for collectible card games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "pcgrl procedural content generation via reinforcement learning")
  Member "improving hearthstone ai by combining mcts and supervised learning algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "covariance matrix adaptation for the rapid illumination of behavior space")
  Member "helping ai to play hearthstone aaia 17 data mining challenge":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the many ai challenges of hearthstone")
  Member "demonstrating the feasibility of automatic game balancing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "evolutionary approach to collectible card game arena deckbuilding using active genes")
  Member "robots that can adapt like animals":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "explore discover and learn unsupervised discovery of state covering skills")
  Member "evolving a behavioral repertoire for a walking robot":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "fast online adaptation in robotics through meta learning embeddings of simulated priors")

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.NE(Neural and Evolutionary Computing)