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: "on the complexity of trial and error"
  Abstract: Motivated by certain applications from physics, biochemistry, economics, and computer science, in which the objects under investigation are not accessible because of various limitations, we propose a trial-and-error model to examine algorithmic issues in such situations. Given a search problem with a hidden input, we are asked to find a valid solution, to find which we can propose candidate solutions (trials), and use observed violations (errors), to prepare future proposals. In accordance with our motivating applications, we consider the fairly broad class of constraint satisfaction problems, and assume that errors are signaled by a verification oracle in the format of the index of a violated constraint (with the content of the constraint still hidden). #R##N#Our discoveries are summarized as follows. On one hand, despite the seemingly very little information provided by the verification oracle, efficient algorithms do exist for a number of important problems. For the Nash, Core, Stable Matching, and SAT problems, the unknown-input versions are as hard as the corresponding known-input versions, up to a factor of polynomial. We further give almost tight bounds on the latter two problems' trial complexities. On the other hand, there are problems whose complexities are substantially increased in the unknown-input model. In particular, no time-efficient algorithms exist (under standard hardness assumptions) for Graph Isomorphism and Group Isomorphism problems. The tools used to achieve these results include order theory, strong ellipsoid method, and some non-standard reductions. #R##N#Our model investigates the value of information, and our results demonstrate that the lack of input information can introduce various levels of extra difficulty. The model exhibits intimate connections with (and we hope can also serve as a useful supplement to) certain existing learning and complexity theories.

Connected through hyperedge HE-1 (induced by source paper "the dependent doors problem an investigation into sequential decisions without feedback"):
  with members:
    - "searching on trees with noisy memory"
    - "deterministic and probabilistic binary search in graphs"
    - "toward more localized local algorithms removing assumptions concerning global knowledge"

Connected through hyperedge HE-2 (induced by source paper "on the complexity of probabilistic trials for hidden satisfiability problems"):
  with members:
    - "solving linear programming with constraints unknown"

Connected through hyperedge HE-3 (induced by source paper "the sampling and learning framework a statistical view of evolutionary algorithms"):
  with members:
    - "performance analysis of evolutionary algorithms for the minimum label spanning tree problem"
    - "multiplicative drift analysis"
    - "more effective crossover operators for the all pairs shortest path problem"
    - "parameterized runtime analyses of evolutionary algorithms for the euclidean traveling salesperson problem"
    - "on the approximation ability of evolutionary optimization with application to minimum set cover"
    - "a new method for lower bounds on the running time of evolutionary algorithms"
    - "multi view active learning in the non realizable case"

Connected through hyperedge HE-4 (induced by source paper "a stable marriage requires communication"):
  with members:
    - "no stable matching mechanism is obviously strategy proof"
    - "stable matching mechanisms are not obviously strategy proof"
    - "fast distributed almost stable marriages"
    - "economic efficiency requires interaction"
    - "manipulation of stable matchings using minimal blacklists"

Connected through hyperedge HE-5 (induced by source paper "on the complexity of trial and error for constraint satisfaction problems"):
  with members:
    - "solving linear programming with constraints unknown"

Connected through hyperedge HE-6 (induced by source paper "learning equilibria of games via payoff queries"):
  with members:
    - "the query complexity of correlated equilibria"
    - "finding approximate nash equilibria of bimatrix games via payoff queries"
    - "graphical models for game theory"
    - "on the communication complexity of approximate nash equilibria"
    - "query complexity of approximate nash equilibria"
    - "query complexity of correlated equilibrium"
    - "approximate well supported nash equilibria below two thirds"
    - "on oblivious ptas s for nash equilibrium"

Connected through hyperedge HE-7 (induced by source paper "solving linear programming with constraints unknown"):
  with members:
    - "on the complexity of trial and error for constraint satisfaction problems"

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.CC(Computational Complexity)