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: "computational curiosity a book draft"
  Abstract: This book discusses computational curiosity, from the psychology of curiosity to the computational models of curiosity, and then showcases several interesting applications of computational curiosity. A brief overview of the book is given as follows. Chapter 1 discusses the underpinnings of curiosity in human beings, including the major categories of curiosity, curiosity-related emotions and behaviors, and the benefits of curiosity. Chapter 2 reviews the arousal theories of curiosity in psychology and summarizes a general two-step process model for computational curiosity. Base on the perspective of the two-step process model, Chapter 3 reviews and analyzes some of the traditional computational models of curiosity. Chapter 4 introduces a novel generic computational model of curiosity, which is developed based on the arousal theories of curiosity. After the discussion of computational models of curiosity, we outline the important applications where computational curiosity may bring significant impacts in Chapter 5. Chapter 6 discusses the application of the generic computational model of curiosity in a machine learning framework. Chapter 7 discusses the application of the generic computational model of curiosity in a recommender system. In Chapter 8 and Chapter 9, the generic computational model of curiosity is studied in two types of pedagogical agents. In Chapter 8, a curious peer learner is studied. It is a non-player character that aims to provide a believable virtual learning environment for users. In Chapter 9, a curious learning companion is studied. It aims to enhance users' learning experience through providing meaningful interactions with them. Chapter 10 discusses open questions in the research field of computation curiosity.

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)