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 "reasoning about hypothetical agent behaviours and their parameters"):
  Abstract: Agents can achieve effective interaction with previously unknown other agents by maintaining beliefs over a set of hypothetical behaviours, or types, that these agents may have. A current limitation in this method is that it does not recognise parameters within type specifications, because types are viewed as blackbox mappings from interaction histories to probability distributions over actions. In this work, we propose a general method which allows an agent to reason about both the relative likelihood of types and the values of any bounded continuous parameters within types. The method maintains individual parameter estimates for each type and selectively updates the estimates for some types after each observation. We propose different methods for the selection of types and the estimation of parameter values. The proposed methods are evaluated in detailed experiments, showing that updating the parameter estimates of a single type after each observation can be sufficient to achieve good performance.

Includes members:
  Member "on convergence and optimality of best response learning with policy types in multiagent systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "are you doing what i think you are doing criticising uncertain agent models")
  Member "belief and truth in hypothesised behaviours":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "integrating planning and interpretable goal recognition for autonomous driving")
  Member "exploiting causality for selective belief filtering in dynamic bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "autonomous agents modelling other agents a comprehensive survey and open problems")
  Member "a game theoretic model and best response learning method for ad hoc coordination in multiagent systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "autonomous industrial management via reinforcement learning self learning agents for decision making a review")
  Member "team behavior in interactive dynamic influence diagrams with applications to ad hoc teams":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "teaching social behavior through human reinforcement for ad hoc teamwork the star framework")
  Member "bayesopt a bayesian optimization library for nonlinear optimization experimental design and bandits":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "automated machine learning state of the art and open challenges")
  Member "tractable inference for complex stochastic processes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "explaining deep neural networks with a polynomial time algorithm for shapley values approximation")
  Member "the factored frontier algorithm for approximate inference in dbns":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "factored probabilistic belief tracking")

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)