human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "multi vehicle collision avoidance via hamilton jacobi reachability and mixed integer programming"
  Abstract: Multi-agent differential games are important and useful tools for analyzing many practical problems, such as air traffic management and multi-vehicle collision avoidance. With the recent surge of interest in using UAVs for civil purposes, the importance and urgency of developing tractable multi-agent analysis techniques that provide safety and performance guarantees is at an all-time high. Hamilton-Jacobi (HJ) reachability has successfully provided safety guarantees to small-scale systems and is flexible in terms of system dynamics. However, the exponential complexity scaling of HJ reachability prevents its direct application to large scale problems when the number of vehicles is greater than two. In this paper, we overcome the scalability limitations of HJ reachability by using a mixed integer program that exploits the properties of HJ solutions to provide higher-level control logic. Our proposed method provides safety guarantee for three-vehicle systems -- a previously intractable task for HJ reachability -- without incurring significant additional computation cost. Furthermore, our method is scalable beyond three vehicles and performs significantly better by several metrics than an extension of pairwise collision avoidance to multi-vehicle collision avoidance. We demonstrate our proposed method in simulations.

Connected through hyperedge HE-1 (induced by source paper "ttr based rewards for reinforcement learning with implicit model priors"):
  with members:
    - "barc backward reachability curriculum for robotic reinforcement learning"
    - "feudal networks for hierarchical reinforcement learning"
    - "reverse curriculum generation for reinforcement learning"
    - "reachability based safety and goal satisfaction of unmanned aerial platoons on air highways"
    - "proximal policy optimization algorithms"
    - "deep exploration via bootstrapped dqn"
    - "exploration a study of count based exploration for deep reinforcement learning"
    - "hierarchical deep reinforcement learning integrating temporal abstraction and intrinsic motivation"

Connected through hyperedge HE-2 (induced by source paper "a scalable framework for real time multi robot multi human collision avoidance"):
  with members:
    - "classification based approximate reachability with guarantees applied to safe trajectory tracking"
    - "a classification based approach for approximate reachability"
    - "probabilistically safe robot planning with confidence based human predictions"
    - "bridging the gap between safety and real time performance in receding horizon trajectory design for mobile robots"
    - "robust tracking with model mismatch for fast and safe planning an sos optimization approach"
    - "cooperative multi agent planning a survey"
    - "planning fast and slow a framework for adaptive real time safe trajectory planning"
    - "fastrack a modular framework for fast and guaranteed safe motion planning"

Connected through hyperedge HE-3 (induced by source paper "hamilton jacobi reachability a brief overview and recent advances"):
  with members:
    - "recursive regression with neural networks approximating the hji pde solution"
    - "a general safety framework for learning based control in uncertain robotic systems"
    - "reachability based safety and goal satisfaction of unmanned aerial platoons on air highways"
    - "fastrack a modular framework for fast and guaranteed safe motion planning"
    - "provably safe and robust drone routing via sequential path planning a case study in san francisco and the bay area"
    - "funnel libraries for real time robust feedback motion planning"
    - "using neural networks to compute approximate and guaranteed feasible hamilton jacobi bellman pde solutions"
    - "safe sequential path planning of multi vehicle systems under presence of disturbances and imperfect information"

Connected through hyperedge HE-4 (induced by source paper "safe and resilient multi vehicle trajectory planning under adversarial intruder"):
  with members:
    - "fastrack a modular framework for fast and guaranteed safe motion planning"
    - "safe sequential path planning of multi vehicle systems under presence of disturbances and imperfect information"
    - "safe sequential path planning of multi vehicle systems via double obstacle hamilton jacobi isaacs variational inequality"

Question: Please tell me which class the center node 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.SY(Systems and Control)