human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "policy synthesis for factored mdps with graph temporal logic specifications"):
  Abstract: We study the synthesis of policies for multi-agent systems to implement spatial-temporal tasks. We formalize the problem as a factored Markov decision process subject to so-called graph temporal logic specifications. The transition function and the spatial-temporal task of each agent depend on the agent itself and its neighboring agents. The structure in the model and the specifications enable to develop a distributed algorithm that, given a factored Markov decision process and a graph temporal logic formula, decomposes the synthesis problem into a set of smaller synthesis problems, one for each agent. We prove that the algorithm runs in time linear in the total number of agents. The size of the synthesis problem for each agent is exponential only in the number of neighboring agents, which is typically much smaller than the number of agents. We demonstrate the algorithm in case studies on disease control and urban security. The numerical examples show that the algorithm can scale to hundreds of agents.

Includes members:
  Member "graph temporal logic inference for classification and identification":
    also connected through other hyperedges:
      (none)
  Member "reward based deception with cognitive bias":
    also connected through other hyperedges:
      (none)
  Member "motion and cooperative transportation planning for multi agent systems under temporal logic formulas":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mode switching decentralized multi agent coordination under local temporal logic tasks")
  Member "omega regular objectives in model free reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reward shaping for reinforcement learning with omega regular objectives")
  Member "environment independent task specifications via gltl":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "extended markov games to learn multiple tasks in multi agent reinforcement learning")
  Member "the robotarium a remotely accessible swarm robotics research testbed":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "what can robotics research learn from computer vision research")
  Member "robotic swarm control from spatio temporal specifications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a graph based spatial temporal logic for knowledge representation and automated reasoning in cognitive robots")
  Member "efficient solution algorithms for factored mdps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "model based multi agent reinforcement learning with cooperative prioritized sweeping")

Question: Please tell me which class the source paper 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.MA(Multiagent Systems)