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: "sapa a multi objective metric temporal planner"
  Abstract: Sapa is a domain-independent heuristic forward chaining planner that can handle durative actions, metric resource constraints, and deadline goals. It is designed to be capable of handling the multi-objective nature of metric temporal planning. Our technical contributions include (i) planning-graph based methods for deriving heuristics that are sensitive to both cost and makespan (ii) techniques for adjusting the heuristic estimates to take action interactions and metric resource limitations into account and (iii) a linear time greedy post-processing technique to improve execution flexibility of the solution plans. An implementation of Sapa using many of the techniques presented in this paper was one of the best domain independent planners for domains with metric and temporal constraints in the third International Planning Competition, held at AIPS-02. We describe the technical details of extracting the heuristics and present an empirical evaluation of the current implementation of Sapa.

Connected through hyperedge HE-1 (induced by source paper "interactive plan explicability in human robot teaming"):
  with members:
    - "ai challenges in human robot cognitive teaming"
    - "plan explanations as model reconciliation moving beyond explanation as soliloquy"
    - "plan explicability and predictability for robot task planning"

Connected through hyperedge HE-2 (induced by source paper "human machine collaborative optimization via apprenticeship scheduling"):
  with members:
    - "convergence of value aggregation for imitation learning"
    - "object manipulation learning by imitation"
    - "active learning of inverse models with intrinsically motivated goal exploration in robots"
    - "a reduction of imitation learning and structured prediction to no regret online learning"
    - "uncertainty in soft temporal constraint problems a general framework and controllability algorithms for the fuzzy case"
    - "how the landscape of random job shop scheduling instances depends on the ratio of jobs to machines"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-3 (induced by source paper "a hybrid lp rpg heuristic for modelling numeric resource flows in planning"):
  with members:
    - "colin planning with continuous linear numeric change"
    - "the lama planner guiding cost based anytime planning with landmarks"
    - "loosely coupled formulations for automated planning an integer programming perspective"
    - "an approach to temporal planning and scheduling in domains with predictable exogenous events"
    - "the deterministic part of ipc 4 an overview"
    - "ordered landmarks in planning"
    - "taming numbers and durations in the model checking integrated planning system"
    - "pddl2 1 an extension to pddl for expressing temporal planning domains"

Connected through hyperedge HE-4 (induced by source paper "quality measures of parameter tuning for aggregated multi objective temporal planning"):
  with members:
    - "multi objective ai planning evaluating dae yahsp on a tunable benchmark"
    - "divide and evolve a new memetic scheme for domain independent temporal planning"

Connected through hyperedge HE-5 (induced by source paper "multi objective ai planning comparing aggregation and pareto approaches"):
  with members:
    - "multi objective ai planning evaluating dae yahsp on a tunable benchmark"
    - "divide and evolve a new memetic scheme for domain independent temporal planning"

Connected through hyperedge HE-6 (induced by source paper "colin planning with continuous linear numeric change"):
  with members:
    - "the lama planner guiding cost based anytime planning with landmarks"
    - "compiling uncertainty away in conformant planning problems with bounded width"
    - "a heuristic search approach to planning with continuous resources in stochastic domains"
    - "modelling mixed discrete continuous domains for planning"
    - "the fast downward planning system"
    - "an approach to temporal planning and scheduling in domains with predictable exogenous events"
    - "the deterministic part of ipc 4 an overview"
    - "taming numbers and durations in the model checking integrated planning system"

Connected through hyperedge HE-7 (induced by source paper "multi objective ai planning evaluating dae yahsp on a tunable benchmark"):
  with members:
    - "divide and evolve a new memetic scheme for domain independent temporal planning"

Connected through hyperedge HE-8 (induced by source paper "on line planning and scheduling an application to controlling modular printers"):
  with members:
    - "regression with respect to sensing actions and partial states"
    - "pddl2 1 an extension to pddl for expressing temporal planning domains"
    - "planning through stochastic local search and temporal action graphs in lpg"
    - "the ff planning system fast plan generation through heuristic search"
    - "on reasonable and forced goal orderings and their use in an agenda driven planning algorithm"
    - "decision theoretic planning structural assumptions and computational leverage"
    - "the automatic inference of state invariants in tim"

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)