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: "where ignoring delete lists works local search topology in planning benchmarks"
  Abstract: Between 1998 and 2004, the planning community has seen vast progress in terms of the sizes of benchmark examples that domain-independent planners can tackle successfully. The key technique behind this progress is the use of heuristic functions based on relaxing the planning task at hand, where the relaxation is to assume that all delete lists are empty. The unprecedented success of such methods, in many commonly used benchmark examples, calls for an understanding of what classes of domains these methods are well suited for. In the investigation at hand, we derive a formal background to such an understanding. We perform a case study covering a range of 30 commonly used STRIPS and ADL benchmark domains, including all examples used in the first four international planning competitions. We prove connections between domain structure and local search topology – heuristic cost surface properties – under an idealized version of the heuristic functions used in modern planners. The idealized heuristic function is called h + , and differs from the practically used functions in that it returns the length of an optimal relaxed plan, which is NP-hard to compute. We identify several key characteristics of the topology under h + , concerning the existence/non-existence of unrecognized dead ends, as well as the existence/non-existence of constant upper bounds on the difficulty of escaping local minima and benches. These distinctions divide the (set of all) planning domains into a taxonomy of classes of varying h + topology. As it turns out, many of the 30 investigated domains lie in classes with a relatively easy topology. Most particularly, 12 of the domains lie in classes where FF’s search algorithm, provided with h + , is a polynomial solving mechanism. We also present results relating h + to its approximation as implemented in FF. The behavior regarding dead ends is provably the same. We summarize the results of an empirical investigation showing that, in many domains, the topological qualities of h + are largely inherited by the approximation. The overall investigation gives a rare example of a successful analysis of the connections between typical-case problem structure, and search performance. The theoretical investigation also gives hints on how the topological phenomena might be automatically recognizable by domain analysis techniques. We outline some preliminary steps we made into that direction.

Connected through hyperedge HE-1 (induced by source paper "learning to rank for synthesizing planning heuristics"):
  with members:
    - "the fast downward planning system"
    - "the ff planning system fast plan generation through heuristic search"

Connected through hyperedge HE-2 (induced by source paper "the complexity of planning revisited a parameterized analysis"):
  with members:
    - "augmenting tractable fragments of abstract argumentation"
    - "the complexity of planning problems with simple causal graphs"
    - "taming numbers and durations in the model checking integrated planning system"
    - "structure and complexity in planning with unary operators"

Connected through hyperedge HE-3 (induced by source paper "avoiding and escaping depressions in real time heuristic search"):
  with members:
    - "cost based satisficing search considered harmful"
    - "case based subgoaling in real time heuristic search for video game pathfinding"
    - "learning in real time search a unifying framework"
    - "learning for adaptive real time search"

Connected through hyperedge HE-4 (induced by source paper "analyzing search topology without running any search on the connection between causal graphs and h"):
  with members:
    - "the lama planner guiding cost based anytime planning with landmarks"
    - "planning over chain causal graphs for variables with domains of size 5 is np hard"
    - "the complexity of planning problems with simple causal graphs"
    - "the fast downward planning system"
    - "ordered landmarks in planning"
    - "structure and complexity in planning with unary operators"
    - "planning through stochastic local search and temporal action graphs in lpg"
    - "the ff planning system fast plan generation through heuristic search"

Connected through hyperedge HE-5 (induced by source paper "message based web service composition integrity constraints and planning under uncertainty a new connection"):
  with members:
    - "the fast downward planning system"
    - "planning graph heuristics for belief space search"
    - "pddl2 1 an extension to pddl for expressing temporal planning domains"
    - "a logic programming approach to knowledge state planning ii the dlv k system"
    - "the 3rd international planning competition results and analysis"
    - "planning through stochastic local search and temporal action graphs in lpg"
    - "the ff planning system fast plan generation through heuristic search"

Connected through hyperedge HE-6 (induced by source paper "structure and problem hardness goal asymmetry and dpll proofs in sat based planning"):
  with members:
    - "engineering benchmarks for planning the domains used in the deterministic part of ipc 4"
    - "the deterministic part of ipc 4 an overview"
    - "beyond hypertree width decomposition methods without decompositions"
    - "ordered landmarks in planning"
    - "towards understanding and harnessing the potential of clause learning"
    - "the 3rd international planning competition results and analysis"
    - "planning through stochastic local search and temporal action graphs in lpg"
    - "a critical assessment of benchmark comparison in planning"

Connected through hyperedge HE-7 (induced by source paper "marvin a heuristic search planner with online macro action learning"):
  with members:
    - "the fast downward planning system"
    - "macro ff improving ai planning with automatically learned macro operators"
    - "the deterministic part of ipc 4 an overview"
    - "the 3rd international planning competition results and analysis"
    - "the ff planning system fast plan generation through heuristic search"
    - "efficient implementation of the plan graph in stan"

Connected through hyperedge HE-8 (induced by source paper "engineering benchmarks for planning the domains used in the deterministic part of ipc 4"):
  with members:
    - "supply restoration in power distribution systems a case study in integrating model based diagnosis and repair planning"
    - "the fast downward planning system"
    - "an approach to temporal planning and scheduling in domains with predictable exogenous events"
    - "the deterministic part of ipc 4 an overview"
    - "taming numbers and durations in the model checking integrated planning system"
    - "pddl2 1 an extension to pddl for expressing temporal planning domains"
    - "the metric ff planning system translating ignoring delete lists to numeric state variables"
    - "the 3rd international planning competition results and analysis"

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)