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: "artificial ant colonies in digital image habitats a mass behaviour effect study on pattern recognition"
  Abstract: Some recent studies have pointed that, the self-organization of neurons into brain-like structures, and the self-organization of ants into a swarm are similar in many respects. If possible to implement, these features could lead to important developments in pattern recognition systems, where perceptive capabilities can emerge and evolve from the interaction of many simple local rules. The principle of the method is inspired by the work of Chialvo and Millonas who developed the first numerical simulation in which swarm cognitive map formation could be explained. From this point, an extended model is presented in order to deal with digital image habitats, in which artificial ants could be able to react to the environment and perceive it. Evolution of pheromone fields point that artificial ant colonies could react and adapt appropriately to any type of digital habitat. KEYWORDS: Swarm Intelligence, Self-Organization, Stigmergy, Artificial Ant Systems, Pattern Recognition and Perception, Image Segmentation, Gestalt Perception Theory, Distributed Computation.

Connected through hyperedge HE-1 (induced by source paper "evolving a stigmergic self organized data mining"):
  with members:
    - "self organizing the abstract canvas as a swarm habitat for collective memory perception and cooperative distributed creativity"
    - "self organized stigmergic document maps environment as a mechanism for context learning"
    - "on the implicit and on the artificial morphogenesis and emergent aesthetics in autonomous collective systems"
    - "business intelligence from web usage mining"
    - "web usage mining using artificial ant colony clustering and linear genetic programming"
    - "swarms on continuous data"
    - "web mining research a survey"

Connected through hyperedge HE-2 (induced by source paper "swarming around shellfish larvae"):
  with members:
    - "from feature extraction to classification a multidisciplinary approach applied to portuguese granites"
    - "self organized stigmergic document maps environment as a mechanism for context learning"
    - "evolving a stigmergic self organized data mining"
    - "web usage mining using artificial ant colony clustering and linear genetic programming"
    - "swarms on continuous data"

Connected through hyperedge HE-3 (induced by source paper "antids self organized ant based clustering model for intrusion detection system"):
  with members:
    - "from feature extraction to classification a multidisciplinary approach applied to portuguese granites"
    - "self organized stigmergic document maps environment as a mechanism for context learning"
    - "evolving a stigmergic self organized data mining"
    - "web usage mining using artificial ant colony clustering and linear genetic programming"
    - "swarms on continuous data"

Connected through hyperedge HE-4 (induced by source paper "self organized stigmergic document maps environment as a mechanism for context learning"):
  with members:
    - "the biological concept of neoteny in evolutionary colour image segmentation simple experiments in simple non memetic genetic algorithms"

Connected through hyperedge HE-5 (induced by source paper "web usage mining using artificial ant colony clustering and linear genetic programming"):
  with members:
    - "self organized stigmergic document maps environment as a mechanism for context learning"
    - "web mining research a survey"

Connected through hyperedge HE-6 (induced by source paper "swarms on continuous data"):
  with members:
    - "from feature extraction to classification a multidisciplinary approach applied to portuguese granites"
    - "self organized stigmergic document maps environment as a mechanism for context learning"

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)