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: "responsibility and blame a structural model approach"
  Abstract: Causality is typically treated an all-or-nothing concept; either A is a cause of B or it is not. We extend the definition of causality introduced by Halpern and Pearl [2001] to take into account the degree of responsibility of A for B. For example, if someone wins an election 11--0, then each person who votes for him is less responsible for the victory than if he had won 6--5. We then define a notion of degree of blame, which takes into account an agent's epistemic state. Roughly speaking, the degree of blame of A for B is the expected degree of responsibility of A for B, taken over the epistemic state of an agent.

Connected through hyperedge HE-1 (induced by source paper "causality based explanation of classification outcomes"):
  with members:
    - "the shapley value of tuples in query answering"
    - "explaining classifiers with causal concept effect cace"
    - "explainable ai for trees from local explanations to global understanding"
    - "an interpretable model with globally consistent explanations for credit risk"
    - "a unified approach to interpreting model predictions"
    - "the mythos of model interpretability"
    - "why should i trust you explaining the predictions of any classifier"
    - "the complexity of causality and responsibility for query answers and non answers"

Connected through hyperedge HE-2 (induced by source paper "efficiently checking actual causality with sat solving"):
  with members:
    - "theoretical impediments to machine learning with seven sparks from the causal revolution"
    - "towards formal definitions of blameworthiness intention and moral responsibility"
    - "understanding and formalizing accountability for cyber physical systems"
    - "from causes for database queries to repairs and model based diagnosis and back"
    - "a modification of the halpern pearl definition of causality"
    - "the computational complexity of structure based causality"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "what causes a system to satisfy a specification"

Connected through hyperedge HE-3 (induced by source paper "responsibility analysis by abstract interpretation"):
  with members:
    - "a relational logic for higher order programs"
    - "cause clue clauses error localization using maximum satisfiability"
    - "provenance as dependency analysis"
    - "what causes a system to satisfy a specification"

Connected through hyperedge HE-4 (induced by source paper "the causality repair connection in databases causality programs"):
  with members:
    - "consistency and trust in peer data exchange systems"
    - "quantifying causal effects on query answering in databases"
    - "causes for query answers from databases datalog abduction view updates and integrity constraints"
    - "achieving data privacy through secrecy views and null based virtual updates"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "design and implementation of aggregate functions in the dlv system"
    - "the dlv system for knowledge representation and reasoning"
    - "answer sets for consistent query answering in inconsistent databases"

Connected through hyperedge HE-5 (induced by source paper "explanation in artificial intelligence insights from the social sciences"):
  with members:
    - "the challenge of crafting intelligible intelligence"
    - "plan explanations as model reconciliation moving beyond explanation as soliloquy"
    - "the mythos of model interpretability"
    - "why should i trust you explaining the predictions of any classifier"
    - "axiomatizing causal reasoning"
    - "causes and explanations in the structural model approach tractable cases"
    - "causes and explanations a structural model approach part ii explanations"

Connected through hyperedge HE-6 (induced by source paper "causes for query answers from databases datalog abduction view updates and integrity constraints"):
  with members:
    - "quantifying causal effects on query answering in databases"
    - "causes for query answers from databases datalog abduction and view updates the presence of integrity constraints"
    - "query answer causality in databases abductive diagnosis and view updates"
    - "from causes for database queries to repairs and model based diagnosis and back"
    - "achieving data privacy through secrecy views and null based virtual updates"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"
    - "coherent integration of databases by abductive logic programming"

Connected through hyperedge HE-7 (induced by source paper "quantifying causal effects on query answering in databases"):
  with members:
    - "causes for query answers from databases datalog abduction and view updates the presence of integrity constraints"
    - "query answer causality in databases abductive diagnosis and view updates"
    - "from causes for database queries to repairs and model based diagnosis and back"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "causality and the semantics of provenance"

Connected through hyperedge HE-8 (induced by source paper "causality and responsibility for formal verification and beyond"):
  with members:
    - "a modification of the halpern pearl definition of causality"
    - "what causes a system to satisfy a specification"
    - "causes and explanations a structural model approach part ii explanations"

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)