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: "the price of uncertainty in present biased planning"
  Abstract: The tendency to overestimate immediate utility is a common cognitive bias. As a result people behave inconsistently over time and fail to reach long-term goals. Behavioral economics tries to help affected individuals by implementing external incentives. However, designing robust incentives is often difficult due to imperfect knowledge of the parameter $\beta \in (0,1]$ quantifying a person's present bias. Using the graphical model of Kleinberg and Oren, we approach this problem from an algorithmic perspective. Based on the assumption that the only information about $\beta$ is its membership in some set $B \subset (0,1]$, we distinguish between two models of uncertainty: one in which $\beta$ is fixed and one in which it varies over time. As our main result we show that the conceptual loss of efficiency incurred by incentives in the form of penalty fees is at most $2$ in the former and $1 + \max B/\min B$ in the latter model. We also give asymptotically matching lower bounds and approximation algorithms.

Connected through hyperedge HE-1 (induced by source paper "time inconsistent planning simple motivation is hard to find"):
  with members:
    - "planning with multiple biases"
    - "on the value of penalties in time inconsistent planning"
    - "motivating time inconsistent agents a computational approach"
    - "planning problems for sophisticated agents with present bias"
    - "time inconsistent planning a computational problem in behavioral economics"

Connected through hyperedge HE-2 (induced by source paper "combinatorial auctions with endowment effect"):
  with members:
    - "the communication complexity of local search"
    - "planning with multiple biases"
    - "on the value of penalties in time inconsistent planning"
    - "motivating time inconsistent agents a computational approach"
    - "procrastination with variable present bias"
    - "planning problems for sophisticated agents with present bias"
    - "computational issues in time inconsistent planning"
    - "time inconsistent planning a computational problem in behavioral economics"

Connected through hyperedge HE-3 (induced by source paper "motivating time inconsistent agents a computational approach"):
  with members:
    - "planning with multiple biases"
    - "on the value of penalties in time inconsistent planning"
    - "procrastination with variable present bias"
    - "planning problems for sophisticated agents with present bias"
    - "computational issues in time inconsistent planning"
    - "time inconsistent planning a computational problem in behavioral economics"

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.GT(Computer Science and Game Theory)