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 "social influence as intrinsic motivation for multi agent deep reinforcement learning"):
  Abstract: We propose a unified mechanism for achieving coordination and communication in Multi-Agent Reinforcement Learning (MARL), through rewarding agents for having causal influence over other agents' actions. Causal influence is assessed using counterfactual reasoning. At each timestep, an agent simulates alternate actions that it could have taken, and computes their effect on the behavior of other agents. Actions that lead to bigger changes in other agents' behavior are considered influential and are rewarded. We show that this is equivalent to rewarding agents for having high mutual information between their actions. Empirical results demonstrate that influence leads to enhanced coordination and communication in challenging social dilemma environments, dramatically increasing the learning curves of the deep RL agents, and leading to more meaningful learned communication protocols. The influence rewards for all agents can be computed in a decentralized way by enabling agents to learn a model of other agents using deep neural networks. In contrast, key previous works on emergent communication in the MARL setting were unable to learn diverse policies in a decentralized manner and had to resort to centralized training. Consequently, the influence reward opens up a window of new opportunities for research in this area.

Includes members:
  Member "learning to share and hide intentions using information regularization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exploiting hierarchy for learning and transfer in kl regularized rl")
  Member "compositional obverter communication learning from raw visual input":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "emergent communication with world models")
  Member "new and surprising ways to be mean adversarial npcs with coupled empowerment minimisation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "maven multi agent variational exploration")
  Member "emergence of communication in an interactive world with consistent speakers":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "emergent communication with world models")
  Member "measuring collaborative emergent behavior in multi agent reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "promoting coordination through policy regularization in multi agent deep reinforcement learning")
  Member "emergence of linguistic communication from referential games with symbolic and pixel input":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "machine theory of mind":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "cooperating with machines":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi agent reinforcement learning and human social factors in climate change mitigation")

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.LG(Machine Learning)