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: "exploiting subgraph structure in multi robot path planning"
  Abstract: Multi-robot path planning is dificult due to the combinatorial explosion of the search space with every new robot added. Complete search of the combined state-space soon becomes intractable. In this paper we present a novel form of abstraction that allows us to plan much more eficiently. The key to this abstraction is the partitioning of the map into subgraphs of known structure with entry and exit restrictions which we can represent compactly. Planning then becomes a search in the much smaller space of subgraph configurations. Once an abstract plan is found, it can be quickly resolved into a correct (but possibly sub-optimal) concrete plan without the need for further search. We prove that this technique is sound and complete and demonstrate its practical effiectiveness on a real map.#R##N##R##N#A contending solution, prioritised planning, is also evaluated and shown to have similar performance albeit at the cost of completeness. The two approaches are not necessarily conflicting; we demonstrate how they can be combined into a single algorithm which out-performs either approach alone.

Connected through hyperedge HE-1 (induced by source paper "multi agent path finding with capacity constraints"):
  with members:
    - "multi agent path finding with deadlines"
    - "lazy modeling of variants of token swapping problem and multi agent path finding through combination of satisfiability modulo theories and conflict based search"
    - "towards search based motion planning for micro aerial vehicles"
    - "overview generalizations of multi agent path finding to real world scenarios"
    - "mapp a scalable multi agent path planning algorithm with tractability and completeness guarantees"

Connected through hyperedge HE-2 (induced by source paper "on the tour towards dpll mapf and beyond"):
  with members:
    - "multi agent pathfinding mapf with continuous time"
    - "multi agent path finding with continuous time viewed through satisfiability modulo theories smt"
    - "multi agent path finding with deadlines"
    - "overview generalizations of multi agent path finding to real world scenarios"
    - "mapp a scalable multi agent path planning algorithm with tractability and completeness guarantees"

Connected through hyperedge HE-3 (induced by source paper "multi agent path finding with continuous time viewed through satisfiability modulo theories smt"):
  with members:
    - "multi agent pathfinding mapf with continuous time"
    - "multi agent path finding with deadlines"
    - "overview generalizations of multi agent path finding to real world scenarios"
    - "optimal multi robot path planning on graphs structure and computational complexity"
    - "mapp a scalable multi agent path planning algorithm with tractability and completeness guarantees"

Connected through hyperedge HE-4 (induced by source paper "x anytime multi agent path finding for sparse domains using iterative repairs"):
  with members:
    - "planning optimal paths for multiple robots on graphs"
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-5 (induced by source paper "finding optimal solutions to token swapping by conflict based search and reduction to sat"):
  with members:
    - "optimal target assignment and path finding for teams of agents"
    - "the time complexity of the token swapping problem and its parallel variants"
    - "complexity of token swapping and its variants"
    - "optimal multi robot path planning on graphs structure and computational complexity"
    - "planning optimal paths for multiple robots on graphs"

Connected through hyperedge HE-6 (induced by source paper "lazy modeling of variants of token swapping problem and multi agent path finding through combination of satisfiability modulo theories and conflict based search"):
  with members:
    - "the time complexity of the token swapping problem and its parallel variants"
    - "optimal multi robot path planning on graphs structure and computational complexity"
    - "planning optimal paths for multiple robots on graphs"

Connected through hyperedge HE-7 (induced by source paper "a summary of adaptation of techniques from search based optimal multi agent path finding solvers to compilation based approach"):
  with members:
    - "planning optimal paths for multiple robots on graphs"
    - "mapp a scalable multi agent path planning algorithm with tractability and completeness guarantees"

Connected through hyperedge HE-8 (induced by source paper "average case constant factor time and distance optimal multi robot path planning in well connected environments"):
  with members:
    - "lifelong multi agent path finding for online pickup and delivery tasks"
    - "sear a polynomial time expected constant factor optimal algorithmic framework for multi robot path planning"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "on the hardness of unlabeled multi robot motion planning"
    - "efficient multi robot motion planning for unlabeled discs in simple polygons"
    - "a linear time algorithm for the feasibility of pebble motion on graphs"
    - "k color multi robot motion planning"
    - "distance optimal formation control on graphs with a tight convergence time guarantee"

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)