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 "near optimal adversarial policy switching for decentralized asynchronous multi agent systems"):
  Abstract: A key challenge in multi-robot and multi-agent systems is generating solutions that are robust to other self-interested or even adversarial parties who actively try to prevent the agents from achieving their goals. The practicality of existing works addressing this challenge is limited to only small-scale synchronous decision-making scenarios or a single agent planning its best response against a single adversary with fixed, procedurally characterized strategies. In contrast this paper considers a more realistic class of problems where a team of asynchronous agents with limited observation and communication capabilities need to compete against multiple strategic adversaries with changing strategies. This problem necessitates agents that can coordinate to detect changes in adversary strategies and plan the best response accordingly. Our approach first optimizes a set of stratagems that represent these best responses. These optimized stratagems are then integrated into a unified policy that can detect and respond when the adversaries change their strategies. The near-optimality of the proposed framework is established theoretically as well as demonstrated empirically in simulation and hardware.

Includes members:
  Member "ssd single shot multibox detector":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "relatext exploiting visual relationships for arbitrary shaped scene text detection with graph convolutional networks")
  Member "decentralized control of partially observable markov decision processes using belief space macro actions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reinforcement learning for pomdp partitioned rollout and policy iteration with application to autonomous sequential repair problems")
  Member "a general framework for interacting bayes optimally with self interested agents using arbitrary parametric model and model prior":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online risk bounded motion planning for autonomous vehicles in dynamic environments")
  Member "interactive pomdp lite towards practical planning to predict and exploit intentions for interacting with self interested agents":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "interactive decision making for autonomous vehicles in dense traffic")
  Member "the complexity of decentralized control of markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "human level performance in 3d multiplayer games with population based reinforcement learning")
  Member "improved memory bounded dynamic programming for decentralized pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on solving cooperative marl problems with a few good experiences")
  Member "maa a heuristic search algorithm for solving decentralized pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a deep actor critic reinforcement learning framework for dynamic multichannel access")
  Member "a framework for sequential planning in multi agent settings":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the hanabi challenge a new frontier for ai 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.AI(Artificial Intelligence)