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: "optimal cost almost sure reachability in pomdps"
  Abstract: We consider partially observable Markov decision processes (POMDPs) with a set of target states and every transition is associated with an integer cost. The optimization objective we study asks to minimize the expected total cost till the target set is reached, while ensuring that the target set is reached almost-surely (with probability 1). We show that for integer costs approximating the optimal cost is undecidable. For positive costs, our results are as follows: (i) we establish matching lower and upper bounds for the optimal cost and the bound is double exponential; (ii) we show that the problem of approximating the optimal cost is decidable and present approximation algorithms developing on the existing algorithms for POMDPs with finite-horizon objectives. While the worst-case running time of our algorithm is double exponential, we also present efficient stopping criteria for the algorithm and show experimentally that it performs well in many examples of interest.

Connected through hyperedge HE-1 (induced by source paper "counterexample driven synthesis for probabilistic program sketches"):
  with members:
    - "shepherding hordes of markov chains"
    - "structured synthesis for probabilistic systems"
    - "safety aware apprenticeship learning"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"
    - "high level counterexamples for probabilistic automata"
    - "safety constrained reinforcement learning for mdps"
    - "a symbolic sat based algorithm for almost sure reachability with small strategies in pomdps"

Connected through hyperedge HE-2 (induced by source paper "strategy synthesis in pomdps via game based abstractions"):
  with members:
    - "human in the loop synthesis for partially observable markov decision processes"
    - "counterexample guided abstraction refinement for pomdps"
    - "a storm is coming a modern probabilistic model checker"
    - "motion planning under partial observability using game based abstraction"
    - "reinforcement learning of pomdps using spectral methods"
    - "qualitative analysis of pomdps with temporal logic specifications for robotics applications"
    - "discretized approximations for pomdp with average cost"
    - "control of probabilistic systems under dynamic partially known environments with temporal logic specifications"

Connected through hyperedge HE-3 (induced by source paper "shepherding hordes of markov chains"):
  with members:
    - "parameter independent strategies for pmdps via pomdps"
    - "reachability in augmented interval markov chains"
    - "a storm is coming a modern probabilistic model checker"
    - "a symbolic sat based algorithm for almost sure reachability with small strategies in pomdps"

Connected through hyperedge HE-4 (induced by source paper "parameter independent strategies for pmdps via pomdps"):
  with members:
    - "sea param exploring schedulers in parametric mdps"
    - "sequential convex programming for the efficient verification of parametric mdps"
    - "automated experiment design for data efficient verification of parametric markov decision processes"
    - "a storm is coming a modern probabilistic model checker"
    - "ares adaptive receding horizon synthesis of optimal plans"
    - "parameter synthesis for markov models faster than ever"
    - "a symbolic sat based algorithm for almost sure reachability with small strategies in pomdps"
    - "pomdps under probabilistic semantics"

Connected through hyperedge HE-5 (induced by source paper "human in the loop synthesis for partially observable markov decision processes"):
  with members:
    - "permissive finite state controllers of pomdps using parameter synthesis"
    - "a storm is coming a modern probabilistic model checker"
    - "motion planning under partial observability using game based abstraction"
    - "synthesis of shared control protocols with provable safety and performance guarantees"
    - "high level counterexamples for probabilistic automata"
    - "qualitative analysis of pomdps with temporal logic specifications for robotics applications"
    - "solving pomdps by searching the space of finite policies"
    - "heuristic search value iteration for pomdps"

Connected through hyperedge HE-6 (induced by source paper "expectation optimization with probabilistic guarantees in pomdps with discounted sum objectives"):
  with members:
    - "variations on the stochastic shortest path problem"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"
    - "heuristic search value iteration for pomdps"
    - "online planning algorithms for pomdps"
    - "reinforcement learning a survey"

Connected through hyperedge HE-7 (induced by source paper "permissive finite state controllers of pomdps using parameter synthesis"):
  with members:
    - "parametric markov chains pctl complexity and fraction free gaussian elimination"
    - "sequential convex programming for the efficient verification of parametric mdps"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"
    - "safety constrained reinforcement learning for mdps"
    - "permissive controller synthesis for probabilistic systems"
    - "a symbolic sat based algorithm for almost sure reachability with small strategies in pomdps"
    - "solving pomdps by searching the space of finite policies"

Connected through hyperedge HE-8 (induced by source paper "motion planning under partial observability using game based abstraction"):
  with members:
    - "counterexample guided abstraction refinement for pomdps"
    - "a storm is coming a modern probabilistic model checker"
    - "qualitative analysis of pomdps with temporal logic specifications for robotics applications"
    - "discretized approximations for pomdp with average cost"
    - "control of probabilistic systems under dynamic partially known environments with temporal logic specifications"
    - "partial observation stochastic games how to win when belief fails"

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)