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: "a job assignment heuristic for lifelong multi agent path finding problem with multiple delivery locations"
  Abstract: Multi-agent path finding (MAPF) algorithms are offline methods intended to find conflict-free paths for more than one agent. However, for many real-life applications, this problem description is inadequate for representing the needs of the domain. To address this issue we worked on a lifelong variation in which agents can have more than one ordered destination. New destinations can be inserted into the system anytime after the initial job-assignment has been made, and these new destinations must also be assigned to agents, and the time of visiting the new destination must also be determined. We called this Lifelong Multi-Agent Path Finding with Multiple Delivery Locations (MAPF-MD). To solve this problem we introduced the Multiple Delivery Conflict-Based Search algorithm (MD-DCBS). We used D*-lite in the low-level search of CBS to benefit from the D*-lite's incremental nature in achieving a performance increase in the CBS search. To handle multiple delivery locations we define multiple D*-lite instances for each agent. The aggregations of all of the paths produced by the D*-lite instances constitute the path of that agent. After that we run CBS on aggregated paths. In this problem we introduced the Multiple Delivery Conflict-Based Search algorithm (MD-DCBS). We used D*-lite in the low-level search of CBS to benefit from the D*-lite's incremental nature in achieving a performance increase in the CBS search. To handle multiple delivery locations we define multiple D*-lite instances for each agent. The aggregations of all of the paths produced by the D*-lite instances constitute the path of that agent. After that we run CBS on aggregated paths. We have shown that this version solves MAPF-MD instances correctly. We also proposed multiple job-assignment heuristics to generate low-total-cost solutions and determined the best performing method amongst them.

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)