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: "theta any angle path planning on grids"
  Abstract: Grids with blocked and unblocked cells are often used to represent terrain in robotics and video games. However, paths formed by grid edges can be longer than true shortest paths in the terrain since their headings are artificially constrained. We present two new correct and complete anyangle path-planning algorithms that avoid this shortcoming. Basic Theta* and Angle-Propagation Theta* are both variants of A* that propagate information along grid edges without constraining paths to grid edges. Basic Theta* is simple to understand and implement, fast and finds short paths. However, it is not guaranteed to find true shortest paths. Angle-Propagation Theta* achieves a better worst-case complexity per vertex expansion than Basic Theta* by propagating angle ranges when it expands vertices, but is more complex, not as fast and finds slightly longer paths. We refer to Basic Theta* and Angle-Propagation Theta* collectively as Theta*. Theta* has unique properties, which we analyze in detail. We show experimentally that it finds shorter paths than both A* with post-smoothed paths and Field D* (the only other version of A* we know of that propagates information along grid edges without constraining paths to grid edges) with a runtime comparable to that of A* on grids. Finally, we extend Theta* to grids that contain unblocked cells with non-uniformtraversal costs and introduce variants of Theta* which provide different tradeoffs between path length and runtime.

Connected through hyperedge HE-1 (induced by source paper "path finding for the coalition of co operative agents acting in the environment with destructible obstacles"):
  with members:
    - "behavior and path planning for the coalition of cognitive robots in smart relocation tasks"
    - "applying mapp algorithm for cooperative path finding in urban environments"
    - "any angle pathfinding for multiple agents based on sipp algorithm"
    - "psychologically inspired planning method for smart relocation task"
    - "mapp a scalable multi agent path planning algorithm with tractability and completeness guarantees"

Connected through hyperedge HE-2 (induced by source paper "perception driven sparse graphs for optimal motion planning"):
  with members:
    - "nanomap fast uncertainty aware proximity queries with lazy search over local 3d data"
    - "a unifying formalism for shortest path problems with expensive edge evaluations via lazy best first search over paths with edge selectors"
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-3 (induced by source paper "elian enhanced algorithm for angle constrained path finding"):
  with members:
    - "grid based angle constrained path planning"

Connected through hyperedge HE-4 (induced by source paper "behavior and path planning for the coalition of cognitive robots in smart relocation tasks"):
  with members:
    - "grid based angle constrained path planning"
    - "the lama planner guiding cost based anytime planning with landmarks"
    - "modelling mixed discrete continuous domains for planning"
    - "the fast downward planning system"
    - "pddl2 1 an extension to pddl for expressing temporal planning domains"
    - "the ff planning system fast plan generation through heuristic search"
    - "the symbol grounding problem"

Connected through hyperedge HE-5 (induced by source paper "any angle pathfinding for multiple agents based on sipp algorithm"):
  with members:
    - "complete decentralized method for on line multi robot trajectory planning in valid infrastructures"
    - "mapp a scalable multi agent path planning algorithm with tractability and completeness guarantees"

Connected through hyperedge HE-6 (induced by source paper "an efficient approach to communication aware path planning for long range surveillance missions undertaken by uavs"):
  with members:
    - "grid based angle constrained path planning"

Connected through hyperedge HE-7 (induced by source paper "a survey of motion planning and control techniques for self driving urban vehicles"):
  with members:
    - "route planning in transportation networks"
    - "optimal sampling based motion planning under differential constraints the driftless case"
    - "discrete and continuous probabilistic anticipation for autonomous robots in urban environments"
    - "sampling based algorithms for optimal motion planning"
    - "anytime heuristic search"

Connected through hyperedge HE-8 (induced by source paper "resolving spatial time conflicts in a set of any angle or angle constrained grid paths"):
  with members:
    - "grid based angle constrained path planning"
    - "proximal operators for multi agent path planning"
    - "mapp a scalable multi agent path planning algorithm with tractability and completeness guarantees"

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.CG(Computational Geometry)