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 "practical linear value approximation techniques for first order mdps"):
  Abstract: Recent work on approximate linear programming (ALP) techniques for first-order Markov Decision Processes (FOMDPs) represents the value function linearly w.r.t. a set of first-order basis functions and uses linear programming techniques to determine suitable weights. This approach offers the advantage that it does not require simplification of the first-order value function, and allows one to solve FOMDPs independent of a specific domain instantiation. In this paper, we address several questions to enhance the applicability of this work: (1) Can we extend the first-order ALP framework to approximate policy iteration to address performance deficiencies of previous approaches? (2) Can we automatically generate basis functions and evaluate their impact on value function quality? (3) How can we decompose intractable problems with universally quantified rewards into tractable subproblems? We propose answers to these questions along with a number of novel optimizations and provide a comparative empirical evaluation on logistics problems from the ICAPS 2004 Probabilistic Planning Competition.

Includes members:
  Member "a heuristic search algorithm for solving first order mdps":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "planning with noisy probabilistic relational rules")
  Member "exploiting first order regression in inductive policy selection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a heuristic search algorithm for solving first order mdps")
  Member "approximate linear programming for first order mdps":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "policy iteration for relational mdps")
  Member "mgpt a probabilistic planner based on heuristic search":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "decision theoretic planning with non markovian rewards")
  Member "efficient solution algorithms for factored mdps":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "policy synthesis for factored mdps with graph temporal logic specifications")
  Member "decision theoretic planning structural assumptions and computational leverage":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal by design model driven synthesis of adaptation strategies for autonomous systems")

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.AI(Artificial Intelligence)