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: "multi sensor information processing using prediction market based belief aggregation"
  Abstract: We considerthe problemofinformation fusion frommultiple sensorsofdiﬀer-ent types with the objective of improving the conﬁdence of inference tasks, suchas object classiﬁcation, performed from the data collected by the sensors. Wepropose a novel technique based on distributed belief aggregation using a multi-agent prediction market to solve this information fusion problem. To monitorthe improvement in the conﬁdence of the object classiﬁcation as well as to dis-incentivize agents from misreporting information, we have introduced a marketmaker that rewards the agents instantaneously as well as at the end of the infer-ence task, based on the quality of the submitted reports. We have implementedthe market maker’s reward calculation in the form of a scoring rule and haveshown analytically that it incentivizes truthful revelation or accurate reportingby each agent. We have experimentally veriﬁed our technique for multi-sensorinformation fusion for an automated landmine detection scenario. Our experi-mental results show that, for identical data distributions and settings, using ourinformation aggregation technique increases the accuracy of object classiﬁcationfavorably as compared to two other commonly used techniques for informationfusion for landmine detection.

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.MA(Multiagent Systems)