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 "graph temporal logic inference for classification and identification"):
  Abstract: Inferring spatial-temporal properties from data is important for many complex systems, such as additive manufacturing systems, swarm robotic systems and biological networks. Such systems can often be modeled as a labeled graph where labels on the nodes and edges represent relevant measurements such as temperatures and distances. We introduce graph temporal logic (GTL) which can express properties such as "whenever a node's label is above 10, for the next 3 time units there are always at least two neighboring nodes with an edge label of at most 2 where the node labels are above 5". This paper is a first attempt to infer spatial (graph) temporal logic formulas from data for classification and identification. For classification, we infer a GTL formula that classifies two sets of graph temporal trajectories with minimal misclassification rate. For identification, we infer a GTL formula that is informative and is satisfied by the graph temporal trajectories in the dataset with high probability. The informativeness of a GTL formula is measured by the information gain with respect to given prior knowledge represented by a prior probability distribution. We implement the proposed approach to classify the graph patterns of tensile specimens built from selective laser sintering (SLS) process with varying strengths, and to identify informative spatial-temporal patterns from experimental data of the SLS cooldown process and simulation data of a swarm of robots.

Includes members:
  Member "information guided temporal logic inference with prior knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adaptive teaching of temporal logic formulas to learners with preferences")
  Member "mining parametric temporal logic properties in model based design for cyber physical systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adaptive teaching of temporal logic formulas to learners with preferences")
  Member "census signal temporal logic inference for multiagent group behavior analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adaptive teaching of temporal logic formulas to learners with preferences")
  Member "learning linear temporal properties":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "adaptive teaching of temporal logic formulas to learners with preferences")
  Member "learning task specifications from demonstrations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adaptive teaching of temporal logic formulas to learners with preferences")
  Member "the robotarium a remotely accessible swarm robotics research testbed":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "what can robotics research learn from computer vision research")

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.LO(Logic in Computer Science)