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: "generalized planning non deterministic abstractions and trajectory constraints"
  Abstract: We study the characterization and computation of general policies for families of problems that share a structure characterized by a common reduction into a single abstract problem. Policies $\mu$ that solve the abstract problem P have been shown to solve all problems Q that reduce to P provided that $\mu$ terminates in Q. In this work, we shed light on why this termination condition is needed and how it can be removed. The key observation is that the abstract problem P captures the common structure among the concrete problems Q that is local (Markovian) but misses common structure that is global. We show how such global structure can be captured by means of trajectory constraints that in many cases can be expressed as LTL formulas, thus reducing generalized planning to LTL synthesis. Moreover, for a broad class of problems that involve integer variables that can be increased or decreased, trajectory constraints can be compiled away, reducing generalized planning to fully observable non-deterministic planning.

Connected through hyperedge HE-1 (induced by source paper "guarantees for sound abstractions for generalized planning extended paper"):
  with members:
    - "features projections and representation change for generalized planning"
    - "learning features and abstract actions for computing generalized plans"
    - "first order decision diagrams for relational mdps"
    - "the automatic inference of state invariants in tim"

Connected through hyperedge HE-2 (induced by source paper "model free model based and general intelligence"):
  with members:
    - "feature based aggregation and deep reinforcement learning a survey and some new implementations"
    - "theoretical impediments to machine learning with seven sparks from the causal revolution"
    - "planning with pixels in almost real time"
    - "features projections and representation change for generalized planning"
    - "deep learning a critical appraisal"
    - "learning generalized reactive policies using deep neural networks"
    - "mastering chess and shogi by self play with a general reinforcement learning algorithm"
    - "thinking fast and slow with deep learning and tree search"

Connected through hyperedge HE-3 (induced by source paper "features projections and representation change for generalized planning"):
  with members:
    - "learning generalized reactive policies using deep neural networks"
    - "learning to navigate in complex environments"
    - "first order decision diagrams for relational mdps"
    - "approximate policy iteration with a policy language bias solving relational markov decision processes"

Connected through hyperedge HE-4 (induced by source paper "on plans with loops and noise"):
  with members:
    - "reasoning about noisy sensors and effectors in the situation calculus"

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.AI(Artificial Intelligence)