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 "resource driven mission phasing techniques for constrained agents in stochastic environments"):
  Abstract: Because an agent's resources dictate what actions it can possibly take, it should plan which resources it holds over time carefully, considering its inherent limitations (such as power or payload restrictions), the competing needs of other agents for the same resources, and the stochastic nature of the environment. Such agents can, in general, achieve more of their objectives if they can use -- and even create -- opportunities to change which resources they hold at various times. Driven by resource constraints, the agents could break their overall missions into an optimal series of phases, optimally reconfiguring their resources at each phase, and optimally using their assigned resources in each phase, given their knowledge of the stochastic environment.#R##N##R##N#In this paper, we formally define and analyze this constrained, sequential optimization problem in both the single-agent and multi-agent contexts. We present a family of mixed integer linear programming (MILP) formulations of this problem that can optimally create phases (when phases are not predefined) accounting for costs and limitations in phase creation. Because our formulations simultaneously also find the optimal allocations of resources at each phase and the optimal policies for using the allocated resources at each phase, they exploit structure across these coupled problems. This allows them to find solutions significantly faster (orders of magnitude faster in larger problems) than alternative solution techniques, as we demonstrate empirically.

Includes members:
  Member "flexible decomposition algorithms for weakly coupled markov decision problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "graying the black box understanding dqns")
  Member "the complexity of decentralized control of markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "human level performance in 3d multiplayer games with population based reinforcement learning")
  Member "resource allocation among agents with mdp induced preferences":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a coordinated mdp approach to multi agent planning for resource allocation with applications to healthcare")
  Member "iterative milp methods for vehicle control problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "collision free navigation of a multi robot team for intruder interception")
  Member "decentralized control of cooperative systems categorization and complexity analysis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning multi agent communication under limited bandwidth restriction for internet packet routing")
  Member "efficient solution algorithms for factored mdps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "policy synthesis for factored mdps with graph temporal logic specifications")
  Member "multiagent control of self reconfigurable robots":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy dissipation by metamorphic micro robots in viscous fluids")
  Member "decision theoretic planning structural assumptions and computational leverage":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimal by design model driven synthesis of adaptation strategies for autonomous systems")

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.MA(Multiagent Systems)