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: "decision theoretic coordination and control for active multi camera surveillance in uncertain partially observable environments"
  Abstract: A central problem of surveillance is to monitor multiple targets moving in a large-scale, obstacle-ridden environment with occlusions. This paper presents a novel principled Partially Observable Markov Decision Process-based approach to coordinating and controlling a network of active cameras for tracking and observing multiple mobile targets at high resolution in such surveillance environments. Our proposed approach is capable of (a) maintaining a belief over the targets' states (i.e., locations, directions, and velocities) to track them, even when they may not be observed directly by the cameras at all times, (b) coordinating the cameras' actions to simultaneously improve the belief over the targets' states and maximize the expected number of targets observed with a guaranteed resolution, and (c) exploiting the inherent structure of our surveillance problem to improve its scalability (i.e., linear time) in the number of targets to be observed. Quantitative comparisons with state-of-the-art multi-camera coordination and control techniques show that our approach can achieve higher surveillance quality in real time. The practical feasibility of our approach is also demonstrated using real AXIS 214 PTZ cameras

Connected through hyperedge HE-1 (induced by source paper "gp localize persistent mobile robot localization using online sparse gaussian process observation model"):
  with members:
    - "gaussian process based decentralized data fusion and active sensing for mobility on demand system"
    - "information theoretic approach to efficient adaptive path planning for mobile robotic environmental sensing"
    - "multi robot informative path planning for active sensing of environmental phenomena a tale of two algorithms"
    - "decentralized data fusion and active sensing with mobile sensors for modeling and predicting spatiotemporal traffic phenomena"
    - "active markov information theoretic path planning for robotic environmental sensing"

Connected through hyperedge HE-2 (induced by source paper "a general framework for interacting bayes optimally with self interested agents using arbitrary parametric model and model prior"):
  with members:
    - "information theoretic approach to efficient adaptive path planning for mobile robotic environmental sensing"
    - "multi robot informative path planning for active sensing of environmental phenomena a tale of two algorithms"
    - "interactive pomdp lite towards practical planning to predict and exploit intentions for interacting with self interested agents"
    - "near optimal brl using optimistic local transitions"
    - "learning is planning near bayes optimal reinforcement learning via monte carlo tree search"
    - "decentralized data fusion and active sensing with mobile sensors for modeling and predicting spatiotemporal traffic phenomena"
    - "active markov information theoretic path planning for robotic environmental sensing"

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)