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 "inference based strategy alignment for general sum differential games"):
  Abstract: In many settings where multiple agents interact, the optimal choices for each agent depend heavily on the choices of the others. These coupled interactions are well-described by a general-sum differential game, in which players have differing objectives, the state evolves in continuous time, and optimal play may be characterized by one of many equilibrium concepts, e.g., a Nash equilibrium. Often, problems admit multiple equilibria. From the perspective of a single agent in such a game, this multiplicity of solutions can introduce uncertainty about how other agents will behave. This paper proposes a general framework for resolving ambiguity between equilibria by reasoning about the equilibrium other agents are aiming for. We demonstrate this framework in simulations of a multi-player human-robot navigation problem that yields two main conclusions: First, by inferring which equilibrium humans are operating at, the robot is able to predict trajectories more accurately, and second, by discovering and aligning itself to this equilibrium the robot is able to reduce the cost for all players.

Includes members:
  Member "on gradient based learning in continuous games":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "local nash equilibria are isolated strict local nash equilibria in almost all zero sum continuous games")
  Member "cooperation aware reinforcement learning for merging in dense traffic":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "survey of deep reinforcement learning for motion planning of autonomous vehicles")
  Member "on finding local nash equilibria and only local nash equilibria in zero sum games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gans may have no nash equilibria")
  Member "on the convergence of gradient based learning in continuous games":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "implicit competitive regularization in gans")
  Member "social gan socially acceptable trajectories with generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")
  Member "hierarchical game theoretic planning for autonomous vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sequential forecasting of 100 000 points")
  Member "a scalable framework for real time multi robot multi human collision avoidance":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "human following for wheeled robot with monocular pan tilt camera")
  Member "the value of inferring the internal state of traffic participants for autonomous freeway driving":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "social attention for autonomous decision making in dense traffic")

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.RO(Robotics)