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: "modeling belief in dynamic systems part i foundations"
  Abstract: Belief change is a fundamental problem in AI: Agents constantly have to update their beliefs to accommodate new observations. In recent years, there has been much work on axiomatic characterizations of belief change. We claim that a better understanding of belief change can be gained from examining appropriate semantic models. In this paper we propose a general framework in which to model belief change. We begin by defining belief in terms of knowledge and plausibility: an agent believes p if he knows that p is more plausible than its negation. We then consider some properties defining the interaction between knowledge and plausibility, and show how these properties affect the properties of belief. In particular, we show that by assuming two of the most natural properties, belief becomes a KD45 operator. Finally, we add time to the picture. This gives us a framework in which we can talk about knowledge, plausibility (and hence belief), and time, which extends the framework of Halpern and Fagin for modeling knowledge in multi-agent systems. We then examine the problem of ``minimal change''. This notion can be captured by using prior plausibilities, an analogue to prior probabilities, which can be updated by ``conditioning''. We show by example that conditioning on a plausibility measure can capture many scenarios of interest. In a companion paper, we show how the two best-studied scenarios of belief change, belief revisionand belief update, fit into our framework.

Connected through hyperedge HE-1 (induced by source paper "reasoning about cognitive trust in stochastic multiagent systems"):
  with members:
    - "a classification model for sensing human trust in machines using eeg and gsr"
    - "a storm is coming a modern probabilistic model checker"

Connected through hyperedge HE-2 (induced by source paper "a knowledge based analysis of global function computation"):
  with members:
    - "knowledge based synthesis of distributed systems using event structures"
    - "using counterfactuals in knowledge based programming"

Connected through hyperedge HE-3 (induced by source paper "outlier detection by logic programming"):
  with members:
    - "the dlv system for knowledge representation and reasoning"
    - "abductive logic programs with penalization semantics complexity and implementation"
    - "unfolding partiality and disjunctions in stable model semantics"
    - "belief revision a critique"

Connected through hyperedge HE-4 (induced by source paper "intransitivity and vagueness"):
  with members:
    - "sleeping beauty reconsidered conditioning and reflection in asynchronous systems"

Connected through hyperedge HE-5 (induced by source paper "modeling belief in dynamic systems part ii revisions and update"):
  with members:
    - "a qualitative markov assumption and its implications for belief change"
    - "nonmonotonic reasoning preferential models and cumulative logics"
    - "belief revision and rational inference"
    - "belief revision a critique"
    - "plausibility measures and default reasoning"

Connected through hyperedge HE-6 (induced by source paper "using counterfactuals in knowledge based programming"):
  with members:
    - "axiomatizing causal reasoning"
    - "knowledge and common knowledge in a distributed environment"

Connected through hyperedge HE-7 (induced by source paper "belief revision a critique"):
  with members:
    - "belief revision and rational inference"

Connected through hyperedge HE-8 (induced by source paper "a counterexample to theorems of cox and fine"):
  with members:
    - "an axiomatic framework for belief updates"
    - "plausibility measures and default reasoning"

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)