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 "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.

Includes members:
  Member "planning with multiple biases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "time inconsistent planning simple motivation is hard to find")
  Member "on the value of penalties in time inconsistent planning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "time inconsistent planning simple motivation is hard to find")
  Member "motivating time inconsistent agents a computational approach":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "time inconsistent planning simple motivation is hard to find")
  Member "procrastination with variable present bias":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "penalty bidding mechanisms for allocating resources and overcoming present bias")
  Member "planning problems for sophisticated agents with present bias":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "time inconsistent planning simple motivation is hard to find")
  Member "time inconsistent planning a computational problem in behavioral economics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "time inconsistent planning simple motivation is hard to find")

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.GT(Computer Science and Game Theory)