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 "incentivizing the emergence of grounded discrete communication between general agents"):
  Abstract: We converted the recently developed BabyAI grid world platform to a sender/receiver setup in order to test the hypothesis that established deep reinforcement learning techniques are sufficient to incentivize the emergence of a grounded discrete communication protocol between general agents. This is in contrast to previous experiments that employed straight-through estimation or tailored inductive biases. Our results show that these can indeed be avoided, by instead providing proper environmental incentives. Moreover, they show that a longer interval between communications incentivized more abstract semantics. In some cases, the communicating agents adapted to new environments more quickly than monolithic agents, showcasing the potential of emergent discrete communication for transfer learning.

Includes members:
  Member "on the pitfalls of measuring emergent communication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "babyai first steps towards grounded language learning with a human in the loop":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "compositional obverter communication learning from raw visual input":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "emergent communication with world models")
  Member "scalable agent alignment via reward modeling a research direction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ai safety state of the field through quantitative lens")
  Member "emergence of linguistic communication from referential games with symbolic and pixel input":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "emergence of language with multi agent games learning to communicate with sequences of symbols":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "natural language does not emerge naturally in multi agent dialog":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "emergence of grounded compositional language in multi agent populations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "improving coordination in small scale multi agent deep reinforcement learning through memory driven communication")

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)