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: "planning under continuous time and resource uncertainty a challenge for ai"
  Abstract: We outline a class of problems, typical of Mars rover operations, that are problematic for current methods of planning under uncertainty. The existing methods fail because they suffer from one or more of the following limitations: 1) they rely on very simple models of actions and time, 2) they assume that uncertainty is manifested in discrete action outcomes, 3) they are only practical for very small problems. For many real world problems, these assumptions fail to hold. In particular, when planning the activities for a Mars rover, none of the above assumptions is valid: 1) actions can be concurrent and have differing durations, 2) there is uncertainty concerning action durations and consumption of continuous resources like power, and 3) typical daily plans involve on the order of a hundred actions. This class of problems may be of particular interest to the UAI community because both classical and decision-theoretic planning techniques may be useful in solving it. We describe the rover problem, discuss previous work on planning under uncertainty, and present a detailed, but very small, example illustrating some of the difficulties of finding good plans.

Connected through hyperedge HE-1 (induced by source paper "fmap distributed cooperative multi agent planning"):
  with members:
    - "an approach to multi agent planning with incomplete information"
    - "a flexible coupling approach to multi agent planning under incomplete information"
    - "the lama planner guiding cost based anytime planning with landmarks"
    - "the 3rd international planning competition results and analysis"
    - "the ff planning system fast plan generation through heuristic search"
    - "partial order planning with concurrent interacting actions"

Connected through hyperedge HE-2 (induced by source paper "bounded approximate symbolic dynamic programming for hybrid mdps"):
  with members:
    - "dynamic programming for structured continuous markov decision problems"
    - "a heuristic search approach to planning with continuous resources in stochastic domains"
    - "solving factored mdps with hybrid state and action variables"
    - "decision theoretic planning structural assumptions and computational leverage"

Connected through hyperedge HE-3 (induced by source paper "symbolic dynamic programming for discrete and continuous state mdps"):
  with members:
    - "spudd stochastic planning using decision diagrams"
    - "dynamic programming for structured continuous markov decision problems"
    - "a heuristic search approach to planning with continuous resources in stochastic domains"
    - "solving factored mdps with hybrid state and action variables"
    - "decision theoretic planning structural assumptions and computational leverage"
    - "exploiting causal independence in bayesian network inference"

Connected through hyperedge HE-4 (induced by source paper "dynamic programming for structured continuous markov decision problems"):
  with members:
    - "incremental pruning a simple fast exact method for partially observable markov decision processes"
    - "spudd stochastic planning using decision diagrams"

Connected through hyperedge HE-5 (induced by source paper "optimal limited contingency planning"):
  with members:
    - "incremental pruning a simple fast exact method for partially observable markov decision processes"
    - "the computational complexity of probabilistic planning"

Connected through hyperedge HE-6 (induced by source paper "topological value iteration algorithms"):
  with members:
    - "on the complexity of solving markov decision problems"
    - "flexible decomposition algorithms for weakly coupled markov decision problems"
    - "hierarchical solution of markov decision processes using macro actions"
    - "the complexity of decentralized control of markov decision processes"
    - "spudd stochastic planning using decision diagrams"
    - "region based incremental pruning for pomdps"
    - "symbolic generalization for on line planning"
    - "a heuristic search approach to planning with continuous resources in stochastic domains"

Connected through hyperedge HE-7 (induced by source paper "resource optimal planning for an autonomous planetary vehicle"):
  with members:
    - "modelling mixed discrete continuous domains for planning"
    - "taming numbers and durations in the model checking integrated planning system"

Connected through hyperedge HE-8 (induced by source paper "certainty closure reliable constraint reasoning with incomplete or erroneous data"):
  with members:
    - "scenario based stochastic constraint programming"
    - "stochastic constraint programming"
    - "stochastic constraint programming a scenario based approach"
    - "efficient solving of quantified inequality constraints over the real numbers"
    - "the essence of constraint propagation"

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)