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 "on greedy and strategic evaders in sequential interdiction settings with incomplete information"):
  Abstract: We consider a class of sequential interdiction settings where the interdictor has incomplete initial information about the network while the evader has complete knowledge of the network, including its structure and arc costs. In each time period, the interdictor can block at most k arcs known to him for the duration of the period. By observing the evader's actions, the interdictor learns about the network structure and costs and thus, can adjust his actions in subsequent time periods. It is known from the literature that if the evader is greedy (i.e., she uses the shortest available path in every time period), then under some assumptions on the the feedback generated from the evader's actions, the greedy interdiction policies that block k-most vital arcs in each time period are efficient and have a finite regret. In this paper, we consider the evader's perspective and explore strategic evasion policies under the assumption that the interdictor is greedy. In particular, we show that the evader's problem is NP-hard even for two time periods. Then we derive constructive properties of optimal evasion policies for two time periods when the interdictor has no initial information about the network structure. Based on these theoretical observations, we design a heuristic algorithm for a strategic evader in a general setting with an arbitrary time horizon and any initial information available to the interdictor initially. Finally, our computational experiments demonstrate that the proposed heuristic consistently outperforms the greedy evasion policy on several classes of synthetic network instances.

Includes members:
  Member "a game of drones cyber physical security of time critical uav applications with cumulative prospect theory perceptions and valuations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "drones in distress a game theoretic countermeasure for protecting uavs against gps spoofing")
  Member "prospect theory for enhanced cyber physical security of drone delivery systems a network interdiction game":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "uav communications for 5g and beyond recent advances and future trends")
  Member "online learning in markov decision processes with adversarially chosen transition probability distributions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "combining no regret and q learning")
  Member "optimal interdiction of unreactive markovian evaders":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "evader interdiction and collateral damage")

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)