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: "a unifying framework for linearly solvable control"
  Abstract: Recent work has led to the development of an elegant theory of Linearly Solvable Markov Decision Processes (LMDPs) and related Path-Integral Control Problems. Traditionally, MDPs have been formulated using stochastic policies and a control cost based on the KL divergence. In this paper, we extend this framework to a more general class of divergences: the Renyi divergences. These are a more general class of divergences parameterized by a continuous parameter that include the KL divergence as a special case. The resulting control problems can be interpreted as solving a risk-sensitive version of the LMDP problem. For a > 0, we get risk-averse behavior (the degree of risk-aversion increases with a) and for a   0. This work generalizes the recently developed risk-sensitive path-integral control formalism which can be seen as the continuous-time limit of results obtained in this paper. To the best of our knowledge, this is a general theory of linearly solvable control and includes all previous work as a special case. We also present an alternative interpretation of these results as solving a 2-player (cooperative or competitive) Markov Game. From the linearity follow a number of nice properties including compositionality of control laws and a path-integral representation of the value function. We demonstrate the usefulness of the framework on control problems with noise where different values of lead to qualitatively different control behaviors.

Connected through hyperedge HE-1 (induced by source paper "optimal load ensemble control in chance constrained optimal power flow"):
  with members:
    - "chance constraints for improving the security of ac optimal power flow"
    - "ensemble control of cycling energy loads markov decision approach"
    - "chance constrained admm approach for decentralized control of distributed energy resources"
    - "optimal ensemble control of loads in distribution grids with network constraints"

Connected through hyperedge HE-2 (induced by source paper "ensemble control of cycling energy loads markov decision approach"):
  with members:
    - "graphical models and belief propagation hierarchy for physics constrained network flows"
    - "structure physics preserving reductions of power grid models"
    - "ensemble of thermostatically controlled loads statistical physics approach"
    - "supervised learning for optimal power flow as a real time proxy"

Connected through hyperedge HE-3 (induced by source paper "information theoretic perspectives on brascamp lieb inequality and its reverse"):
  with members:
    - "arimoto r enyi conditional entropy and bayesian m ary hypothesis testing"
    - "strengthening the entropy power inequality"
    - "algorithmic and optimization aspects of brascamp lieb inequalities via operator scaling"
    - "brascamp lieb inequality and its reverse an information theoretic view"
    - "converses for distributed estimation via strong data processing inequalities"
    - "secret key generation with one communicator and a one shot converse via hypercontractivity"
    - "on non interactive simulation of joint distributions"
    - "a note on the strong data processing inequalities in bayesian networks"

Connected through hyperedge HE-4 (induced by source paper "optimal ensemble control of loads in distribution grids with network constraints"):
  with members:
    - "ensemble control of cycling energy loads markov decision approach"
    - "ensemble of thermostatically controlled loads statistical physics approach"

Connected through hyperedge HE-5 (induced by source paper "ensemble of thermostatically controlled loads statistical physics approach"):
  with members:
    - "ensemble control of cycling energy loads markov decision approach"

Connected through hyperedge HE-6 (induced by source paper "universal convexification via risk aversion"):
  with members:
    - "risk sensitive path integral control"
    - "infinite horizon policy gradient estimation"

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.SY(Systems and Control)