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 "cost bounded active classification using partially observable markov decision processes"):
  Abstract: Active classification, i.e., the sequential decision-making process aimed at data acquisition for classification purposes, arises naturally in many applications, including medical diagnosis, intrusion detection, and object tracking. In this work, we study the problem of actively classifying dynamical systems with a finite set of Markov decision process (MDP) models. We are interested in finding strategies that actively interact with the dynamical system, and observe its reactions so that the true model is determined efficiently with high confidence. To this end, we present a decision-theoretic framework based on partially observable Markov decision processes (POMDPs). The proposed framework relies on assigning a classification belief (a probability distribution) to each candidate MDP model. Given an initial belief, some misclassification probabilities, a cost bound, and a finite time horizon, we design POMDP strategies leading to classification decisions. We present two different approaches to find such strategies. The first approach computes the optimal strategy "exactly" using value iteration. To overcome the computational complexity of finding exact solutions, the second approach is based on adaptive sampling to approximate the optimal probability of reaching a classification decision. We illustrate the proposed methodology using two examples from medical diagnosis and intruder detection.

Includes members:
  Member "barrier certificates for assured machine teaching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "control theory meets pomdps a hybrid systems approach")
  Member "bounded policy synthesis for pomdps with safe reachability objectives":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "point based methods for model checking in partially observable markov decision processes")
  Member "privacy verification in pomdps via barrier certificates":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "control theory meets pomdps a hybrid systems approach")
  Member "pomdp model learning for human robot collaboration":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "incremental learning of discrete planning domains from continuous perceptions")
  Member "synthesis of surveillance strategies via belief abstraction":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "strategy synthesis for surveillance evasion games with learning enabled visibility optimization")
  Member "active classification theory and application to underwater inspection":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "data driven planning via imitation learning")

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.SY(Systems and Control)