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 "teaching social behavior through human reinforcement for ad hoc teamwork the star framework"):
  Abstract: As technology develops, it is only a matter of time before agents will be capable of long-term autonomy, i.e., will need to choose their actions by themselves for a long period of time. Thus, in many cases agents will not be able to be coordinated in advance with all other agents with which they may interact. Instead, agents will need to cooperate in order to accomplish unanticipated joint goals without pre-coordination. As a result, the "ad hoc teamwork" problem, in which teammates must work together to obtain a common goal without any prior agreement regarding how to do so, has emerged as a recent area of study in the AI literature. However, to date, no attention has been dedicated to the social aspect of the agents' behavior, which is required to ensure that their actions' influences on other agents conform with social norms. In this research, we introduce the STAR framework used to teach agents to act in accordance with human social norms with respect to their teammates. Using a hybrid team (agents and people), if taking an action considered to be socially unacceptable, the agents will receive negative feedback from the human teammate(s). We view STAR as an initial step towards achieving the goal of teaching agents to act more consistently with respect to human morality.

Includes members:
  Member "reasoning about hypothetical agent behaviours and their parameters":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exploiting causality for selective belief filtering in dynamic bayesian networks extended abstract")
  Member "incorporating behavioral constraints in online ai systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "how can ai automate end to end data science")
  Member "building ethically bounded ai":
    also connected through other hyperedges:
      (none)
  Member "incomplete contracting and ai alignment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "artificial intelligence values and alignment")
  Member "building ethics into artificial intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bias in data driven ai systems an introductory survey")
  Member "inverse reward design":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "safe imitation learning via fast bayesian reward inference from preferences")
  Member "safe reinforcement learning via shielding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to walk in the real world with minimal human effort")
  Member "belief and truth in hypothesised behaviours":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "integrating planning and interpretable goal recognition for autonomous driving")

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.CY(Computers and Society)