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: "pddl2 1 an extension to pddl for expressing temporal planning domains"
  Abstract: In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling, planetary rover exploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application.#R##N##R##N#The International Planning Competitions have acted as an important motivating force behind the progress that has been made in planning since 1998. The third competition (held in 2002) set the planning community the challenge of handling time and numeric resources. This necessitated the development of a modelling language capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power -- exceeding the capabilities of current planning technology -- and presents a number of important challenges to the research community.

Connected through hyperedge HE-1 (induced by source paper "transferable task execution from pixels through deep planning domain learning"):
  with members:
    - "representing robot task plans as robust logical dynamical systems"
    - "prospection interpretable plans from language by predicting the future"
    - "an intriguing failing of convolutional neural networks and the coordconv solution"
    - "neural task graphs generalizing to unseen tasks from a single video demonstration"
    - "stripstream integrating symbolic planners and blackbox samplers"
    - "peorl integrating symbolic planning and hierarchical reinforcement learning for robust decision making"
    - "one shot hierarchical imitation learning of compound visuomotor tasks"
    - "visual robot task planning"

Connected through hyperedge HE-2 (induced by source paper "deep compositional robotic planners that follow natural language commands"):
  with members:
    - "from semantics to execution integrating action planning with reinforcement learning for robotic causal problem solving"
    - "from language to goals inverse reinforcement learning for vision based instruction following"
    - "from semantics to execution integrating action planning with reinforcement learning for robotic tool use"
    - "prospection interpretable plans from language by predicting the future"
    - "learning to plan via neural exploration exploitation trees"
    - "mapping instructions to actions in 3d environments with visual goal prediction"
    - "deep sequential models for sampling based planning"
    - "follownet robot navigation by following natural language directions with deep reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "spa verbal interactions between agents and avatars in shared virtual environments using propositional planning"):
  with members:
    - "learning language games through interaction"

Connected through hyperedge HE-4 (induced by source paper "3 d scene graph a sparse and semantic representation of physical environments for intelligent agents"):
  with members:
    - "factorizable net an efficient subgraph based framework for scene graph generation"
    - "show and tell lessons learned from the 2015 mscoco image captioning challenge"
    - "pointnet deep hierarchical feature learning on point sets in a metric space"
    - "scene graph generation by iterative message passing"
    - "scene graph generation from objects phrases and region captions"
    - "video captioning with transferred semantic attributes"
    - "hyperface a deep multi task learning framework for face detection landmark localization pose estimation and gender recognition"
    - "graph structured representations for visual question answering"

Connected through hyperedge HE-5 (induced by source paper "online replanning in belief space for partially observable task and motion problems"):
  with members:
    - "deepim deep iterative matching for 6d pose estimation"
    - "representing robot task plans as robust logical dynamical systems"
    - "bounded policy synthesis for pomdps with safe reachability objectives"
    - "sampling based methods for factored task and motion planning"
    - "stripstream integrating symbolic planners and blackbox samplers"
    - "an anytime algorithm for task and motion mdps"
    - "ffrob leveraging symbolic planning for efficient task and motion planning"
    - "posecnn a convolutional neural network for 6d object pose estimation in cluttered scenes"

Connected through hyperedge HE-6 (induced by source paper "online explanation generation for human robot teaming"):
  with members:
    - "progressive explanation generation for human robot teaming"
    - "where do you think you re going inferring beliefs about dynamics from behavior"
    - "explanation in artificial intelligence insights from the social sciences"
    - "ai challenges in human robot cognitive teaming"
    - "plan explanations as model reconciliation moving beyond explanation as soliloquy"
    - "explicablility as minimizing distance from expected behavior"
    - "plan explicability and predictability for robot task planning"

Connected through hyperedge HE-7 (induced by source paper "timeline based planning expressiveness and complexity"):
  with members:
    - "a new rule for ltl tableaux"
    - "sat based explicit ltl reasoning"
    - "an on the fly tableau based decision procedure for pdl satisfiability"
    - "modelling mixed discrete continuous domains for planning"
    - "the ff planning system fast plan generation through heuristic search"
    - "clausal temporal resolution"
    - "the computational complexity of probabilistic planning"

Connected through hyperedge HE-8 (induced by source paper "progressive explanation generation for human robot teaming"):
  with members:
    - "hierarchical expertise level modeling for user specific robot behavior explanations"
    - "explanation in artificial intelligence insights from the social sciences"
    - "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"
    - "the fast downward planning system"

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)